Paper Digest: SIGIR 2015 Highlights
SIGIR (Annual International ACM SIGIR Conference on Research and Development in Information Retrieval) is one of the top information retrieval conferences in the world.
To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper. Readers are encouraged to read these machine generated highlights / summaries to quickly get the main idea of each paper.
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TABLE 1: SIGIR 2015 Papers
| Title | Authors | Highlight | |
|---|---|---|---|
| 1 | Salton Award Lecture: People, Interacting with Information | Nicholas J. Belkin | In this presentation, I will speak at some length on that goal, and on how I think it might be best addressed. |
| 2 | Exploring Session Context using Distributed Representations of Queries and Reformulations | Bhaskar Mitra | In this paper, we study the distributed representation of queries learnt by deep neural network models, such as the Convolutional Latent Semantic Model, and show that they can be used to represent query reformulations as vectors. |
| 3 | An Eye-Tracking Study of Query Reformulation | Carsten Eickhoff, Sebastian Dungs, Vu Tran | In this paper, we study query refinement using eye-tracking in order to gain precise and detailed insight into which terms the user was exposed to in a search session and which ones they showed a particular interest in. |
| 4 | Differences in the Use of Search Assistance for Tasks of Varying Complexity | Robert Capra, Jaime Arguello, Anita Crescenzi, Emily Vardell | In this paper, we study how users interact with a search assistance tool while completing tasks of varying complexity. We collected log data and conducted retrospective stimulated recall interviews to learn about participants’ use of the SG. |
| 5 | Dynamic Query Modeling for Related Content Finding | Daan Odijk, Edgar Meij, Isaac Sijaranamual, Maarten de Rijke | We model this task as a Markov decision process and propose a method that uses reinforcement learning to directly optimize the retrieval effectiveness of queries generated from the stream of subtitles. |
| 6 | Image-Based Recommendations on Styles and Substitutes | Julian McAuley, Christopher Targett, Qinfeng Shi, Anton van den Hengel | We seek here to model this human sense of the relationships between objects based on their appearance. We cast this as a network inference problem defined on graphs of related images, and provide a large-scale dataset for the training and evaluation of the same. |
| 7 | Semi-supervised Hashing with Semantic Confidence for Large Scale Visual Search | Yingwei Pan, Ting Yao, Houqiang Li, Chong-Wah Ngo, Tao Mei | In this paper, we propose a novel semi-supervised hashing framework by leveraging semantic confidence. |
| 8 | Optimal Aggregation Policy for Reducing Tail Latency of Web Search | Jeong-Min Yun, Yuxiong He, Sameh Elnikety, Shaolei Ren | In this paper, we propose aggregation policies that minimize tail latency of search queries subject to search quality service level agreements (SLAs), combining data-driven offline analysis with online processing. |
| 9 | QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees | Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini | Thus, several works already proposed solutions aiming at improving the efficiency of the scoring process by dealing with features and peculiarities of modern CPUs and memory hierarchies. |
| 10 | High Quality Graph-Based Similarity Search | Weiren Yu, Julie Ann McCann | In this paper, we consider high-quality similarity search. |
| 11 | Summarizing Contrastive Themes via Hierarchical Non-Parametric Processes | Zhaochun Ren, Maarten de Rijke | Specifically, we present a hierarchical non-parametric model to describe hierarchical relations among topics; this model is used to infer threads of topics as themes from the nested Chinese restaurant process. |
| 12 | Splitting Water: Precision and Anti-Precision to Reduce Pool Bias | Aldo Lipani, Mihai Lupu, Allan Hanbury | Hence, in this paper we present a new perspective in reducing the pool bias by studying the effect of merging an unpooled run with the pooled runs. |
| 13 | Learning Maximal Marginal Relevance Model via Directly Optimizing Diversity Evaluation Measures | Long Xia, Jun Xu, Yanyan Lan, Jiafeng Guo, Xueqi Cheng | In this paper we address the issue of learning a ranking model for search result diversification. |
| 14 | Analyzing User’s Sequential Behavior in Query Auto-Completion via Markov Processes | Liangda Li, Hongbo Deng, Anlei Dong, Yi Chang, Hongyuan Zha, Ricardo Baeza-Yates | We propose a probabilistic model that addresses those three questions in a unified way, and illustrate how the model determines users’ final click decisions. |
| 15 | Learning by Example: Training Users with High-quality Query Suggestions | Morgan Harvey, Claudia Hauff, David Elsweiler | In this paper we investigate to what extent it is possible to aid users in learning how to formulate better queries by providing examples of high-quality queries interactively during a number of search sessions. |
| 16 | adaQAC: Adaptive Query Auto-Completion via Implicit Negative Feedback | Aston Zhang, Amit Goyal, Weize Kong, Hongbo Deng, Anlei Dong, Yi Chang, Carl A. Gunter, Jiawei Han | We propose a novel adaptive model adaQAC that adapts query auto-completion to users’ implicit negative feedback towards unselected query suggestions. We collect user-QAC interaction data and perform large-scale experiments. |
| 17 | A Random Walk Model for Optimization of Search Impact in Web Frontier Ranking | Giang Tran, Ata Turk, B. Barla Cambazoglu, Wolfgang Nejdl | In this paper, we propose a search-centric solution to the problem of prioritizing the pages in the frontier of a crawler for download. |
| 18 | A Similarity Measure for Weaving Patterns in Textiles | Sven Helmer, Vuong Minh Ngo | We propose a novel approach for measuring the similarity between weaving patterns that can provide similarity-based search functionality for textile archives. |
| 19 | Local Ranking Problem on the BrowseGraph | Michele Trevisiol, Luca Maria Aiello, Paolo Boldi, Roi Blanco | We study the LRP problem on a BrowseGraph from a large news provider, considering as subgraphs the aggregations of browsing traces of users coming from different domains. |
| 20 | How many results per page?: A Study of SERP Size, Search Behavior and User Experience | Diane Kelly, Leif Azzopardi | We found subjects’ click distributions differed significantly depending on SERP size. |
| 21 | Influence of Vertical Result in Web Search Examination | Zeyang Liu, Yiqun Liu, Ke Zhou, Min Zhang, Shaoping Ma | In this paper, we focus on five popular vertical types and try to study their influences on users’ examination processes in both cases when they are relevant or irrelevant to the search queries. |
| 22 | Unconscious Physiological Effects of Search Latency on Users and Their Click Behaviour | Miguel Barreda-Ángeles, Ioannis Arapakis, Xiao Bai, B. Barla Cambazoglu, Alexandre Pereda-Baños | Along the same line, this paper focuses on the user impact of search latency and makes the following two contributions. |
| 23 | Multiple Social Network Learning and Its Application in Volunteerism Tendency Prediction | Xuemeng Song, Liqiang Nie, Luming Zhang, Mohammad Akbari, Tat-Seng Chua | Multiple Social Network Learning and Its Application in Volunteerism Tendency Prediction |
| 24 | HSpam14: A Collection of 14 Million Tweets for Hashtag-Oriented Spam Research | Surendra Sedhai, Aixin Sun | One major contribution of this work is the creation of HSpam14 dataset, which can be used for hashtag-oriented spam research in tweets. |
| 25 | Uncovering Crowdsourced Manipulation of Online Reviews | Amir Fayazi, Kyumin Lee, James Caverlee, Anna Squicciarini | (ii) Second, we augment this base set of deceptive reviewers through a reviewer-reviewer graph clustering approach based on a Markov Random Field where we define individual potentials (of single reviewers) and pair potentials (between two reviewers). |
| 26 | Relevance Scores for Triples from Type-Like Relations | Hannah Bast, Björn Buchhold, Elmar Haussmann | We propose a variety of algorithms to compute these scores. |
| 27 | Fielded Sequential Dependence Model for Ad-Hoc Entity Retrieval in the Web of Data | Nikita Zhiltsov, Alexander Kotov, Fedor Nikolaev | In this work, we propose a novel retrieval model that incorporates term dependencies into structured document retrieval and apply it to the task of ERWD. |
| 28 | Mining, Ranking and Recommending Entity Aspects | Ridho Reinanda, Edgar Meij, Maarten de Rijke | In this paper we focus on the tasks of identifying, ranking, and recommending entity aspects, and propose an approach that mines, clusters, and ranks such aspects from query logs. |
| 29 | Bayesian Ranker Comparison Based on Historical User Interactions | Artem Grotov, Shimon Whiteson, Maarten de Rijke | Specifically, we propose a Bayesian approach for (1) comparing the production ranker to candidate rankers and (2) estimating the confidence of this comparison. |
| 30 | Incorporating Non-sequential Behavior into Click Models | Chao Wang, Yiqun Liu, Meng Wang, Ke Zhou, Jian-yun Nie, Shaoping Ma | In this paper, we investigate the problem of properly incorporating non-sequential behavior into click models. |
| 31 | Untangling Result List Refinement and Ranking Quality: a Framework for Evaluation and Prediction | Jiyin He, Marc Bron, Arjen de Vries, Leif Azzopardi, Maarten de Rijke | In our framework we model user interaction as switching between different sublists. |
| 32 | WEMAREC: Accurate and Scalable Recommendation through Weighted and Ensemble Matrix Approximation | Chao Chen, Dongsheng Li, Yingying Zhao, Qin Lv, Li Shang | This paper presents WEMAREC, a weighted and ensemble matrix approximation method for accurate and scalable recommendation. |
| 33 | Effective Latent Models for Binary Feedback in Recommender Systems | Maksims Volkovs, Guang Wei Yu | We address this problem and propose a new latent approach for binary feedback in CF. In our model, neighborhood similarity information is used to guide latent factorization and derive accurate latent representations. |
| 34 | Personalized Recommendation via Parameter-Free Contextual Bandits | Liang Tang, Yexi Jiang, Lei Li, Chunqiu Zeng, Tao Li | In this paper, we formulate personalized recommendation as a contextual bandit problem to solve the exploration/exploitation dilemma. |
| 35 | An Efficient and Scalable MetaFeature-based Document Classification Approach based on Massively Parallel Computing | Sérgio Canuto, Marcos Gonçalves, Wisllay Santos, Thierson Rosa, Wellington Martins | We take advantage of the current manycore GPU architecture and present a massively parallel version of the kNN algorithm for highly dimensional and sparse datasets (which is the case for ADC). |
| 36 | Listwise Collaborative Filtering | Shanshan Huang, Shuaiqiang Wang, Tie-Yan Liu, Jun Ma, Zhumin Chen, Jari Veijalainen | In this paper, we propose a new ranking-oriented CF algorithm, called ListCF. |
| 37 | BROOF: Exploiting Out-of-Bag Errors, Boosting and Random Forests for Effective Automated Classification | Thiago Salles, Marcos Gonçalves, Victor Rodrigues, Leonardo Rocha | In this work we propose to combine both strategies in order to exploit their strengths while simultaneously solving some of their drawbacks, especially when applied to high-dimensional and noisy classification tasks. |
| 38 | Monolingual and Cross-Lingual Information Retrieval Models Based on (Bilingual) Word Embeddings | Ivan Vulić, Marie-Francine Moens | We propose a new unified framework for monolingual (MoIR) and cross-lingual information retrieval (CLIR) which relies on the induction of dense real-valued word vectors known as word embeddings (WE) from comparable data. |
| 39 | Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks | Aliaksei Severyn, Alessandro Moschitti | In this paper, we present a convolutional neural network architecture for reranking pairs of short texts, where we learn the optimal representation of text pairs and a similarity function to relate them in a supervised way from the available training data. |
| 40 | Context- and Content-aware Embeddings for Query Rewriting in Sponsored Search | Mihajlo Grbovic, Nemanja Djuric, Vladan Radosavljevic, Fabrizio Silvestri, Narayan Bhamidipati | To this end, we propose rewriting method based on a novel query embedding algorithm, which jointly models query content as well as its context within a search session. |
| 41 | Retrieval of Relevant Opinion Sentences for New Products | Dae Hoon Park, Hyun Duk Kim, ChengXiang Zhai, Lifan Guo | Our key idea is to leverage product specifications to assess product similarity between the query product and other products and extract relevant opinion sentences from the similar products where a consumer may find useful discussions. |
| 42 | Learning Hierarchical Representation Model for NextBasket Recommendation | Pengfei Wang, Jiafeng Guo, Yanyan Lan, Jun Xu, Shengxian Wan, Xueqi Cheng | To tackle the above problems, in this paper, we introduce a novel recommendation approach, namely hierarchical representation model (HRM). |
| 43 | Parametric and Non-parametric User-aware Sentiment Topic Models | Zaihan Yang, Alexander Kotov, Aravind Mohan, Shiyong Lu | To address this deficiency, in this paper, we propose parametric and non-parametric User-aware Sentiment Topic Models (USTM) that incorporate demographic information of review authors into topic modeling process in order to discover associations between market segments, topical aspects and sentiments. |
| 44 | Learning to Extract Local Events from the Web | John Foley, Michael Bendersky, Vanja Josifovski | The goal of this work is extraction and retrieval of local events from web pages. |
| 45 | Rank-GeoFM: A Ranking based Geographical Factorization Method for Point of Interest Recommendation | Xutao Li, Gao Cong, Xiao-Li Li, Tuan-Anh Nguyen Pham, Shonali Krishnaswamy | In this paper, we propose a ranking based geographical factorization method, called Rank-GeoFM, for POI recommendation, which addresses the two challenges. |
| 46 | GeoSoCa: Exploiting Geographical, Social and Categorical Correlations for Point-of-Interest Recommendations | Jia-Dong Zhang, Chi-Yin Chow | To tackle this challenge, in this study we propose a new POI recommendation approach called GeoSoCa through exploiting geographical correlations, social correlations and categorical correlations among users and POIs. |
| 47 | Optimised Scheduling of Online Experiments | Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis | In this paper, we formulate the novel problem of schedule optimisation for the queue of the online experiments: given a limited number of the user interactions available for experimentation, we want to re-order the queue so that the number of successful experiments is maximised. |
| 48 | Predicting Search Satisfaction Metrics with Interleaved Comparisons | Anne Schuth, Katja Hofmann, Filip Radlinski | In this paper we present the first method for integrating user satisfaction metrics with interleaving. |
| 49 | Sequential Testing for Early Stopping of Online Experiments | Eugene Kharitonov, Aleksandr Vorobev, Craig Macdonald, Pavel Serdyukov, Iadh Ounis | In this work, we study the usefulness of sequential testing procedures for both interleaving and A/B testing. |
| 50 | Inferring Searcher Attention by Jointly Modeling User Interactions and Content Salience | Dmitry Lagun, Eugene Agichtein | Specifically, we propose a principled model for predicting a searcher’s gaze position on a page, that we call Mixture of Interactions and Content Salience (MICS). |
| 51 | Different Users, Different Opinions: Predicting Search Satisfaction with Mouse Movement Information | Yiqun Liu, Ye Chen, Jinhui Tang, Jiashen Sun, Min Zhang, Shaoping Ma, Xuan Zhu | Inspired by recent studies in predicting result relevance based on mouse movement patterns (namely motifs), we propose to estimate the utilities of search results and the efforts in search sessions with motifs extracted from mouse movement data on search result pages (SERPs). |
| 52 | Predicting Search Intent Based on Pre-Search Context | Weize Kong, Rui Li, Jie Luo, Aston Zhang, Yi Chang, James Allan | In this paper, we propose to study this important but less explored problem. |
| 53 | Leveraging Procedural Knowledge for Task-oriented Search | Zi Yang, Eric Nyberg | We propose to create a three-way parallel corpus of queries, query contexts, and task descriptions, and reduce both problems to sequence labeling tasks. We propose a set of textual features and structural features to identify key search phrases from task descriptions, and then adapt similar features to extract wikiHow-style procedural knowledge descriptions from search queries and relevant text snippets. |
| 54 | Personalizing Search on Shared Devices | Ryen W. White, Ahmed Hassan Awadallah | We present an oracle study (with perfect knowledge of which searchers perform each action on each machine) to under-stand the effectiveness of ABP in predicting searchers’ future interests. |
| 55 | Leveraging User Reviews to Improve Accuracy for Mobile App Retrieval | Dae Hoon Park, Mengwen Liu, ChengXiang Zhai, Haohong Wang | Our key idea is to leverage user reviews to find out important features of apps and bridge vocabulary gap between app developers and users. |
| 56 | Towards a Game-Theoretic Framework for Information Retrieval | ChengXiang Zhai | In this talk, I will present a new game-theoretic formulation of the IR problem where the key idea is to model information retrieval as a process of a search engine and a user playing a cooperative game, with a shared goal of satisfying the user’s information need (or more generally helping the user complete a task) while minimizing the user’s effort and the resource overhead on the retrieval system. |
| 57 | Representative & Informative Query Selection for Learning to Rank using Submodular Functions | Rishabh Mehrotra, Emine Yilmaz | In this work, we investigate query selection strategies for learning to rank aimed at actively selecting unlabelled queries to be labelled so as to minimize the data annotation cost. |
| 58 | Impact of Surrogate Assessments on High-Recall Retrieval | Adam Roegiest, Gordon V. Cormack, Charles L.A. Clarke, Maura R. Grossman | Previous studies suggest that surrogate assessments may be a reasonable proxy for authoritative assessments for this task. |
| 59 | The Benefits of Magnitude Estimation Relevance Assessments for Information Retrieval Evaluation | Andrew Turpin, Falk Scholer, Stefano Mizzaro, Eddy Maddalena | We investigate the use of magnitude estimation for judging the relevance of documents in the context of information retrieval evaluation, carrying out a large-scale user study across 18 TREC topics and collecting more than 50,000 magnitude estimation judgments. |
| 60 | Learning to Reweight Terms with Distributed Representations | Guoqing Zheng, Jamie Callan | In this paper, we propose to address query interpretation and term weighting in a unified framework built upon distributed representations of words from recent advances in neural network language modeling. |
| 61 | A Probabilistic Model for Information Retrieval Based on Maximum Value Distribution | Jiaul H. Paik | In this article, we introduce a new probabilistic model of ranking that addresses the above issues. |
| 62 | Non-Compositional Term Dependence for Information Retrieval | Christina Lioma, Jakob Grue Simonsen, Birger Larsen, Niels Dalum Hansen | Motivated by this lack of distinction between the frequency and strength of term dependence in IR, we present a principled approach for handling term dependence in queries, using both lexical frequency and semantic evidence. |
| 63 | On the Relation Between Assessor’s Agreement and Accuracy in Gamified Relevance Assessment | Olga Megorskaya, Vladimir Kukushkin, Pavel Serdyukov | In this paper, we investigate, whether the agreement level can be used as a metric for estimating the quality of assessor’s judgments, and provide recommendations for the design of judgments collection workflow. |
| 64 | Assessor Differences and User Preferences in Tweet Timeline Generation | Yulu Wang, Garrick Sherman, Jimmy Lin, Miles Efron | This paper tackles the last two questions about assessor differences and user preferences in the context of the newly-introduced tweet timeline generation task in the TREC 2014 Microblog track, where the system’s goal is to construct an informative summary of non-redundant tweets that addresses the user’s information need. |
| 65 | User Variability and IR System Evaluation | Peter Bailey, Alistair Moffat, Falk Scholer, Paul Thomas | By executing those queries, we demonstrate that query formulation is critical to query effectiveness. |
| 66 | An Entity Class-Dependent Discriminative Mixture Model for Cumulative Citation Recommendation | Jingang Wang, Dandan Song, Qifan Wang, Zhiwei Zhang, Luo Si, Lejian Liao, Chin-Yew Lin | In this paper, we propose a novel entity class-dependent discriminative mixture model by introducing a latent entity class layer to model the correlations between entities and latent entity classes. |
| 67 | Scientific Information Understanding via Open Educational Resources (OER) | Xiaozhong Liu, Zhuoren Jiang, Liangcai Gao | Based on the computational information need, we use text mining and heterogeneous graph mining algorithms to recommend high quality OERs to help students better understand the scientific content in the paper. |
| 68 | In Situ Insights | Yuanhua Lv, Ariel Fuxman | In this paper, we study this novel recommendation task, that we call in situ insights: recommending reference concepts in response to a text selection and its context in-situ of a document consumption application. |
| 69 | Islands in the Stream: A Study of Item Recommendation within an Enterprise Social Stream | Ido Guy, Roy Levin, Tal Daniel, Ella Bolshinsky | In this work, we study the recommendation of enterprise social stream items through a user survey with 510 participants, conducted within a globally distributed organization. |
| 70 | Evaluating Streams of Evolving News Events | Gaurav Baruah, Mark D. Smucker, Charles L.A. Clarke | In this paper, we develop a simple model that simulates users checking the system from time to time to read updates. |
| 71 | Information Retrieval as Card Playing: A Formal Model for Optimizing Interactive Retrieval Interface | Yinan Zhang, Chengxiang Zhai | We propose a novel formal model for optimizing interactive information retrieval interfaces. |
| 72 | From Queries to Cards: Re-ranking Proactive Card Recommendations Based on Reactive Search History | Milad Shokouhi, Qi Guo | In this paper, we present the first study on user interactions with information cards. |
| 73 | Using Sensor Metadata Streams to Identify Topics of Local Events in the City | M-Dyaa Albakour, Craig Macdonald, Iadh Ounis | In this paper, we study the emerging Information Retrieval (IR) task of local event retrieval using sensor metadata streams. |
| 74 | StarSum: A Simple Star Graph for Multi-document Summarization | Mohammed Al-Dhelaan | In this paper, we propose StarSum a star bipartite graph which models sentences and their topic signature phrases. |
| 75 | When Relevance Judgement is Happening?: An EEG-based Study | Marco Allegretti, Yashar Moshfeghi, Maria Hadjigeorgieva, Frank E. Pollick, Joemon M. Jose, Gabriella Pasi | For this purpose, we devised a user study in which we captured the brain response of 20 participants. |
| 76 | Search Engine Evaluation based on Search Engine Switching Prediction | Olga Arkhipova, Lidia Grauer, Igor Kuralenok, Pavel Serdyukov | In this paper we present a novel application of the search engine switching prediction model for online evaluation. |
| 77 | Time-Aware Authorship Attribution for Short Text Streams | Hosein Azarbonyad, Mostafa Dehghani, Maarten Marx, Jaap Kamps | In this paper, we analyse the temporal changes of word usage by authors of tweets and emails and based on this analysis we propose an approach to estimate the dynamicity of authors’ word usage. |
| 78 | A Priori Relevance Based On Quality and Diversity Of Social Signals | Ismail Badache, Mohand Boughanem | In this paper, we are particularly interested in: first, showing the impact of signals diversity associated to a resource on information retrieval performance; second, studying the influence of their social networks origin on their quality. |
| 79 | Document Comprehensiveness and User Preferences in Novelty Search Tasks | Ashraf Bah, Praveen Chandar, Ben Carterette | In this paper, we conduct a user study where users are asked to give a preference between one of two documents B and C given a query and also given that they have already seen a document A. |
| 80 | Cost-Aware Result Caching for Meta-Search Engines | Emre Bakkal, Ismail Sengor Altingovde, Ismail Hakki Toroslu | Our goal in this paper is to design cost-aware result caching approaches for meta-search engines. |
| 81 | From Unlabelled Tweets to Twitter-specific Opinion Words | Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer | In this article, we propose a word-level classification model for automatically generating a Twitter-specific opinion lexicon from a corpus of unlabelled tweets. |
| 82 | The Best Published Result is Random: Sequential Testing and its Effect on Reported Effectiveness | Ben Carterette | We argue that the best known published effectiveness on any given collection could be measured as much as 20% higher than its "true" intrinsic effectiveness, and that there are many other systems with lower measured effectiveness that could have substantially higher intrinsic effectiveness. |
| 83 | Load-sensitive CPU Power Management for Web Search Engines | Matteo Catena, Craig Macdonald, Nicola Tonellotto | In this work, we propose to delegate CPU power management to search engine-specific governors. |
| 84 | Retrieval from Noisy E-Discovery Corpus in the Absence of Training Data | Anirban Chakraborty, Kripabandhu Ghosh, Swapan Kumar Parui | We propose a novel algorithm for detecting OCR errors and improving retrieval performance on an E-Discovery corpus. |
| 85 | Opinion Spammer Detection in Web Forum | Yu-Ren Chen, Hsin-Hsi Chen | In this paper, a real case study on opinion spammer detection in web forum is presented. |
| 86 | Multi-Faceted Recall of Continuous Active Learning for Technology-Assisted Review | Gordon V. Cormack, Maura R. Grossman | Through simulations using Cormack and Grossman’s TAR Evaluation Toolkit (SIGIR 2014), we show that continuous active learning, applied to a multi-faceted topic, efficiently achieves high recall for each facet of the topic. |
| 87 | Time Pressure and System Delays in Information Search | Anita Crescenzi, Diane Kelly, Leif Azzopardi | We report preliminary results of the impact of time pressure and system delays on search behavior from a laboratory study with forty-three participants. |
| 88 | How Random Decisions Affect Selective Distributed Search | Zhuyun Dai, Yubin Kim, Jamie Callan | The resource selection algorithm might use a different random sample of the corpus. |
| 89 | Comparing Approaches for Query Autocompletion | Giovanni Di Santo, Richard McCreadie, Craig Macdonald, Iadh Ounis | Hence, in this paper, we present a comparison study between current approaches to rank candidate query completions for the user query as it is typed. |
| 90 | Sign-Aware Periodicity Metrics of User Engagement for Online Search Quality Evaluation | Alexey Drutsa | We propose to overcome this sign-agnostic issue by paying attention to the phase of the corresponding DFT sine wave. |
| 91 | Modelling Term Dependence with Copulas | Carsten Eickhoff, Arjen P. de Vries, Thomas Hofmann | Making use of the formal copula framework, we describe the strength of causal dependency in terms of a number of established term co-occurrence metrics. |
| 92 | Modeling Website Topic Cohesion at Scale to Improve Webpage Classification | Dhivya Eswaran, Paul N. Bennett, Joseph J. Pfeiffer | To this end, we introduce an approach which adjusts a page content-only classification from that obtained with a global prior to the posterior obtained by incorporating a prior which reflects the topic cohesion of the site. |
| 93 | Topic-centric Classification of Twitter User’s Political Orientation | Anjie Fang, Iadh Ounis, Philip Habel, Craig Macdonald, Nut Limsopatham | In this paper, we aim to classify people’s voting intentions by the content of their tweets—their short messages communicated on Twitter. |
| 94 | Word Embedding based Generalized Language Model for Information Retrieval | Debasis Ganguly, Dwaipayan Roy, Mandar Mitra, Gareth J.F. Jones | In this paper, we focus on using the word embeddings for enhancing retrieval effectiveness. |
| 95 | A Head-Weighted Gap-Sensitive Correlation Coefficient | Ning Gao, Douglas Oard | This paper introduces a new measure, τGAP, which combines both features. |
| 96 | On Term Selection Techniques for Patent Prior Art Search | Mona Golestan Far, Scott Sanner, Mohamed Reda Bouadjenek, Gabriela Ferraro, David Hawking | In this paper, we investigate the influence of term selection on retrieval performance on the CLEF-IP prior art test collection, using the Description section of the patent query with Language Model (LM) and BM25 scoring functions. |
| 97 | Automatic Feature Generation on Heterogeneous Graph for Music Recommendation | Chun Guo, Xiaozhong Liu | In this paper, we propose a novel approach to solve the music recommendation problem by means of heterogeneous graph mining. |
| 98 | Differences in Eye-Tracking Measures Between Visits and Revisits to Relevant and Irrelevant Web Pages | Jacek Gwizdka, Yinglong Zhang | This short paper presents initial results from a project, in which we investigated differences in how users view relevant and irrelevant Web pages on their visits and revisits. |
| 99 | Reducing Hubness: A Cause of Vulnerability in Recommender Systems | Kazuo Hara, Ikumi Suzuki, Kei Kobayashi, Kenji Fukumizu | In this paper, we demonstrate that hubness, which occurs in high dimensional data, is exploited by the attacks. |
| 100 | Modularity-Based Query Clustering for Identifying Users Sharing a Common Condition | Maayan Gal-On Harel, Elad Yom-Tov | We present an algorithm for identifying users who share a common condition from anonymized search engine logs. |
| 101 | Understanding Temporal Query Intent | Mohammed Hasanuzzaman, Sriparna Saha, Gaël Dias, Stéphane Ferrari | In this paper, we propose a multi-objective ensemble learning solution that (1) allows to accurately classify queries along their temporal intent and (2) identifies a set of performing solutions thus offering a wide range of possible applications. |
| 102 | On the Reusability of Open Test Collections | Seyyed Hadi Hashemi, Charles L.A. Clarke, Adriel Dean-Hall, Jaap Kamps, Julia Kiseleva | On the Reusability of Open Test Collections |
| 103 | Towards Vandalism Detection in Knowledge Bases: Corpus Construction and Analysis | Stefan Heindorf, Martin Potthast, Benno Stein, Gregor Engels | We report on the construction of the Wikidata Vandalism Corpus WDVC-2015, the first corpus for vandalism in knowledge bases. |
| 104 | About the ‘Compromised Information Need’ and Optimal Interaction as Quality Measure for Search Interfaces | Eduard C. Hoenkamp | Hence we propose a formal definition of levels of information need, as especially in IR with its formal underpinnings, there is no excuse to leave frequently used terms undefined. |
| 105 | I See You: Person-of-Interest Search in Social Networks | Hsun-Ping Hsieh, Cheng-Te Li, Rui Yan | Assume each user is associated a set of social labels, we propose a novel search in online social network, Person-of-Interest (POI) Search, which aims to find a list of desired targets based on a set of user-specified query labels that depict the targets. |
| 106 | Towards Quantifying the Impact of Non-Uniform Information Access in Collaborative Information Retrieval | Nyi Nyi Htun, Martin Halvey, Lynne Baillie | To address this shortcoming, in this paper, we present the results of a simulated evaluation conducted over 4 different non-uniform information access scenarios and 3 different collaborative search strategies. |
| 107 | Features of Disagreement Between Retrieval Effectiveness Measures | Timothy Jones, Paul Thomas, Falk Scholer, Mark Sanderson | In this work, we examine how and where metrics disagree, and identify differences that should be considered when selecting metrics for use in evaluating retrieval systems. |
| 108 | Subsequence Search in Event-Interval Sequences | Orestis Kostakis Kostakis, Aristides Gionis Gionis | We study the problem of subsequence search in databases of event-interval sequences, or e-sequences. |
| 109 | Searcher in a Strange Land: Understanding Web Search from Familiar and Unfamiliar Locations | Elad Kravi, Eugene Agichtein, Ido Guy, Yaron Kanza, Avihai Mejer, Dan Pelleg | In this paper, we argue that information needs are affected by the familiarity of the environment. |
| 110 | Evaluating Retrieval Models through Histogram Analysis | Kriste Krstovski, David A. Smith, Michael J. Kurtz | We present a novel approach for efficiently evaluating the performance of retrieval models and introduce two evaluation metrics: Distributional Overlap (DO), which compares the clustering of scores of relevant and non-relevant documents, and Histogram Slope Analysis (HSA), which examines the log of the empirical distributions of relevant and non-relevant documents. |
| 111 | Inter-Category Variation in Location Search | Chia-Jung Lee, Nick Craswell, Vanessa Murdock | We analyze a large dataset of location searches on GPS-enabled mobile devices with 15 location categories. |
| 112 | Reachability based Ranking in Interactive Image Retrieval | Jiyi Li | In this paper, we propose a new kind of ranking option to users by ranking the images according to their difficulties of reaching potential targets. |
| 113 | Modeling Multi-query Retrieval Tasks Using Density Matrix Transformation | Qiuchi Li, Jingfei Li, Peng Zhang, Dawei Song | In this paper, we propose a Session-based Quantum Language Model (SQLM) that deals with multi-query session search task. |
| 114 | Predicting User Behavior in Display Advertising via Dynamic Collective Matrix Factorization | Sheng Li, Jaya Kawale, Yun Fu | In this paper, we aim to predict the conversion response of users by jointly examining the past purchase behavior and the click response behavior. |
| 115 | Zero-shot Image Tagging by Hierarchical Semantic Embedding | Xirong Li, Shuai Liao, Weiyu Lan, Xiaoyong Du, Gang Yang | This paper proposes Hierarchical Semantic Embedding (HierSE), a simple model that exploits the WordNet hierarchy to improve label embedding and consequently image embedding. |
| 116 | Using Term Location Information to Enhance Probabilistic Information Retrieval | Baiyan Liu, Xiangdong An, Jimmy Xiangji Huang | In this paper, we investigate the effects of rewarding terms based on their location in sentences on information retrieval. |
| 117 | Learning Context-aware Latent Representations for Context-aware Collaborative Filtering | Xin Liu, Wei Wu | In this paper, we propose a generic framework to learn context-aware latent representations for context-aware collaborative filtering. |
| 118 | Exploiting User and Business Attributes for Personalized Business Recommendation | Kai Lu, Yi Zhang, Lanbo Zhang, Shuxin Wang | In this paper, we propose an Integrated Bias and Factorization Model (IBFM), which exploits user and business attributes. |
| 119 | Speeding up Document Ranking with Rank-based Features | Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto | In this paper we propose a new family of rank-based features, which extend the original feature vector associated with each query-document pair. |
| 120 | Mining Measured Information from Text | Arun S. Maiya, Dale Visser, Andrew Wan | We present an approach to extract measured information from text (e.g., a $1370~^{\circ}C$ melting point, a BMI greater than 29.9 kg/m$^2$). |
| 121 | An Initial Investigation into Fixed and Adaptive Stopping Strategies | David Maxwell, Leif Azzopardi, Kalervo Järvelin, Heikki Keskustalo | In this paper, we perform a preliminary simulated analysis into the influence of stopping strategies when query quality varies. |
| 122 | Regularised Cross-Modal Hashing | Sean Moran, Victor Lavrenko | In this paper we propose Regularised Cross-Modal Hashing (RCMH) a new cross-modal hashing model that projects annotation and visual feature descriptors into a common Hamming space. |
| 123 | Adapted B-CUBED Metrics to Unbalanced Datasets | Jose G. Moreno, Gaël Dias | In this paper, we present a modified version of B-CUBED metrics to overcome this situation. |
| 124 | A Time-aware Random Walk Model for Finding Important Documents in Web Archives | Tu Ngoc Nguyen, Nattiya Kanhabua, Claudia Niederée, Xiaofei Zhu | For this purpose, we propose a novel random walk-based model that integrates relevance, temporal authority, diversity and time in a unified framework. |
| 125 | A Test Collection for Spoken Gujarati Queries | Douglas W. Oard, Rashmi Sankepally, Jerome White, Aren Jansen, Craig Harman | A Test Collection for Spoken Gujarati Queries |
| 126 | Discovering Experts across Multiple Domains | Aditya Pal | In this paper, we propose an algorithm for finding experts across these different domains. |
| 127 | Using Key Concepts in a Translation Model for Retrieval | Jae Hyun Park, W. Bruce Croft | Detecting the key concepts in a query can be used as the basis for more effective weighting of query terms, but in this paper, we focus on a method of using the key concepts in a translation model for query expansion and retrieval. |
| 128 | On the Cost of Phrase-Based Ranking | Matthias Petri, Alistair Moffat | Effective postings list compression techniques, and the efficiency of postings list processing schemes such as WAND, have significantly improved the practical performance of ranked document retrieval using inverted indexes. |
| 129 | Location-Aware Model for News Events in Social Media | Mauricio Quezada, Vanessa Peña-Araya, Barbara Poblete | In this work we propose a simple model to represent real-world news events using two sources of information: the locations that are mentioned in the event (where the event occurs), and the locations of users that discuss or comment on it. |
| 130 | Exploring Opportunities to Facilitate Serendipity in Search | Ataur Rahman, Max L. Wilson | In this paper, we deployed a working search engine that matched search results with Facebook ‘Like’ data, as a technology probe to examine naturally occurring serendipitous discoveries. |
| 131 | Combining Orthogonal Information in Large-Scale Cross-Language Information Retrieval | Shigehiko Schamoni, Stefan Riezler | We compare these models under various measures of orthogonality, and present an experimental evaluation on two different domains (patents, Wikipedia) and two different language pairs (Japanese-English, German-English). |
| 132 | Tailoring Music Recommendations to Users by Considering Diversity, Mainstreaminess, and Novelty | Markus Schedl, David Hauger | To alleviate this issue, we propose several user features that model aspects of the user’s music listening behavior: diversity, mainstreaminess, and novelty of the user’s music taste. |
| 133 | Challenges of Mathematical Information Retrievalin the NTCIR-11 Math Wikipedia Task | Moritz Schubotz, Abdou Youssef, Volker Markl, Howard S. Cohl | We developed a framework for automatic query generation and immediate evaluation. |
| 134 | Probabilistic Multileave for Online Retrieval Evaluation | Anne Schuth, Robert-Jan Bruintjes, Fritjof Buüttner, Joost van Doorn, Carla Groenland, Harrie Oosterhuis, Cong-Nguyen Tran, Bas Veeling, Jos van der Velde, Roger Wechsler, David Woudenberg, Maarten de Rijke | We propose probabilistic multileave and empirically show that it is highly sensitive and unbiased. |
| 135 | Twitter Sentiment Analysis with Deep Convolutional Neural Networks | Aliaksei Severyn, Alessandro Moschitti | The main contribution of this work is a new model for initializing the parameter weights of the convolutional neural network, which is crucial to train an accurate model while avoiding the need to inject any additional features. |
| 136 | Anchoring and Adjustment in Relevance Estimation | Milad Shokouhi, Ryen White, Emine Yilmaz | In this paper, we present a study of anchoring bias in information retrieval~(IR) settings. |
| 137 | Cognitive Activity during Web Search | Md. Hedayetul Islam Shovon, D (Nanda) Nandagopal, Jia Tina Du, Ramasamy Vijayalakshmi, Bernadine Cocks | By using this approach, we identified that the cognitive activities during the three stages of Web searching are different, with various brain areas becoming more active during the three Web search task stages. |
| 138 | Personalized Semantic Ranking for Collaborative Recommendation | Song Xu, Shu Wu, Liang Wang | To alleviate the limitation of this assumption, in this work, we present a unified framework, named Personalized Semantic Ranking (PSR). |
| 139 | Active Learning for Entity Filtering in Microblog Streams | Damiano Spina, Maria-Hendrike Peetz, Maarten de Rijke | We therefore approach the problem of entity filtering with active learning, thereby reducing the annotation load for experts. |
| 140 | Relevance-aware Filtering of Tuples Sorted by an Attribute Value via Direct Optimization of Search Quality Metrics | Nikita V. Spirin, Mikhail Kuznetsov, Julia Kiseleva, Yaroslav V. Spirin, Pavel A. Izhutov | In this paper we choose a different approach. |
| 141 | Multi-source Information Fusion for Personalized Restaurant Recommendation | Jing Sun, Yun Xiong, Yangyong Zhu, Junming Liu, Chu Guan, Hui Xiong | In this paper, we study the problem of personalized restaurant recommendations. |
| 142 | Joint Matrix Factorization and Manifold-Ranking for Topic-Focused Multi-Document Summarization | Jiwei Tan, Xiaojun Wan, Jianguo Xiao | In this paper, we propose a joint optimization framework, which integrates the manifold-ranking process with a similarity metric learning process. |
| 143 | Towards Understanding the Impact of Length in Web Search Result Summaries over a Speech-only Communication Channel | Johanne R. Trippas, Damiano Spina, Mark Sanderson, Lawrence Cavedon | Based on crowdsourced workers, we found that users preferred longer, more informative summaries for text presentation. |
| 144 | Early Detection of Topical Expertise in Community Question Answering | David van Dijk, Manos Tsagkias, Maarten de Rijke | We use a semi-supervised machine learning approach. |
| 145 | LBMCH: Learning Bridging Mapping for Cross-modal Hashing | Yang Wang, Xuemin Lin, Lin Wu, Wenjie Zhang, Qing Zhang | In this paper, we study the problem of learning hash functions in the context of multi-modal data for cross-modal similarity search. |
| 146 | Gibberish, Assistant, or Master?: Using Tweets Linking to News for Extractive Single-Document Summarization | Zhongyu Wei, Wei Gao | In this paper, we explore effective ways using the tweets linking to news for generating extractive summary of each document. |
| 147 | Context-aware Point-of-Interest Recommendation Using Tensor Factorization with Social Regularization | Lina Yao, Quan Z. Sheng, Yongrui Qin, Xianzhi Wang, Ali Shemshadi, Qi He | To address this new challenge, we propose a Collaborative Filtering method based on Non-negative Tensor Factorization, a generalization of the Matrix Factorization approach that exploits a high-order tensor instead of traditional User-Location matrix to model multi-dimensional contextual information. |
| 148 | Adaptive User Engagement Evaluation via Multi-task Learning | Hamed Zamani, Pooya Moradi, Azadeh Shakery | In this paper, we try to make use of tweets from different web applications to improve the user engagement evaluation performance. |
| 149 | Compact Snippet Caching for Flash-based Search Engines | Rui Zhang, Pengyu Sun, Jiancong Tong, Rebecca Jane Stones, Gang Wang, Xiaoguang Liu | We propose a simple, but effective method for exploiting this trend, which we call fragment caching: instead of caching the whole snippet, we only cache snippet metadata which describe how to retrieve the snippet from the document. |
| 150 | When Personalization Meets Conformity: Collective Similarity based Multi-Domain Recommendation | Xi Zhang, Jian Cheng, Shuang Qiu, Zhenfeng Zhu, Hanqing Lu | In this paper, we establish a Collective Structure Sparse Representation(CSSR) method for multi-domain recommendation. |
| 151 | Sub-document Timestamping of Web Documents | Yue Zhao, Claudia Hauff | In this paper, we investigate to what extent (i) this simplifying assumption is violated for a corpus of Web documents, and, (ii) it is possible to accurately estimate the creation time of individual Web documents’ components (so-called sub-documents). |
| 152 | DINFRA: A One Stop Shop for Computing Multilingual Semantic Relatedness | Siamak Barzegar, Juliano Efson Sales, Andre Freitas, Siegfried Handschuh, Brian Davis | This demonstration presents an infrastructure for computing multilingual semantic relatedness and correlation for twelve natural languages by using three distributional semantic models (DSMs). |
| 153 | VenueMusic: A Venue-Aware Music Recommender System | Zhiyong Cheng, Jialie Shen | In this demonstration, we present an intelligent music recommender system, called VenueMusic, to automatically identify suitable music for various popular venues in our daily lives. |
| 154 | Shiny on Your Crazy Diagonal | Giorgio Maria Di Nunzio | In this demo, we present a web application which allows users to interact with two retrieval models, namely the Binary Independence Model (BIM) and the BM25 model, on a standard TREC collection. |
| 155 | CricketLinking: Linking Event Mentions from Cricket Match Reports to Ball Entities in Commentaries | Manish Gupta | When reading a match report, reader experience can be significantly improved by augmenting (on demand) the event mentions in the report with detailed commentaries. |
| 156 | An Aspect-driven Social Media Explorer | Nedim Lipka, W. Bruce Croft | Unlike existing approaches that group content by trending topics, we present a holistic view of diverse and relevant content with respect to a given query. |
| 157 | ERICA: Expert Guidance in Validating Crowd Answers | Nguyen Quoc Viet Hung, Duong Chi Thang, Matthias Weidlich, Karl Aberer | To support the expert in the validation process, we present a tool for \emph{ExpeRt guidance In validating Crowd Answers (ERICA)}. |
| 158 | Large-scale Image Retrieval using Neural Net Descriptors | David Novak, Michal Batko, Pavel Zezula | Large-scale Image Retrieval using Neural Net Descriptors |
| 159 | Galean: Visualization of Geolocated News Events from Social Media | Vanessa Peña-Araya, Mauricio Quezada, Barbara Poblete | Galean: Visualization of Geolocated News Events from Social Media |
| 160 | SciNet: Interactive Intent Modeling for Information Discovery | Tuukka Ruotsalo, Jaakko Peltonen, Manuel J.A. Eugster, Dorota Głowacka, Aki Reijonen, Giulio Jacucci, Petri Myllymäki, Samuel Kaski | Instead, users are distracted by the need to focus their cognitive efforts on finding navigation cues, rather than selecting relevant information. |
| 161 | Linse: A Distributional Semantics Entity Search Engine | Juliano Efson Sales, André Freitas, Siegfried Handschuh, Brian Davis | In order to address this phenomenon for entity search targeting descriptors for complex categories, we propose a compositional-distributional semantics entity search engine, which extracts semantic and commonsense knowledge from large-scale corpora to address the vocabulary gap between query and data. |
| 162 | Online News Tracking for Ad-Hoc Queries | Jeroen B.P. Vuurens, Arjen P. de Vries, Roi Blanco, Peter Mika | We demonstrate an approach that is feasible for online tracking of news that is relevant to a user’s ad-hoc query. |
| 163 | DUMPLING: A Novel Dynamic Search Engine | Andrew Jie Zhou, Jiyun Luo, Hui Yang | In this demo paper, we introduce a new search engine that supports Information Retrieval (IR) in a dynamic setting. |
| 164 | Promoting User Engagement and Learning in Amorphous Search Tasks | Piyush Arora | Much research in information retrieval (IR) focuses on optimization of the rank of relevant retrieval results for single shot ad hoc IR tasks. |
| 165 | Cross-Platform Question Routing for Better Question Answering | Mossaab Bagdouri | We consider models that work for the general public, before adapting them to some special demographics (Arab journalists). |
| 166 | Time Pressure in Information Search | Anita Crescenzi | The primary purpose of this research is to explore the impact of perceived time pressure on search behaviors, searcher perceptions of the search system and the search experience. |
| 167 | Controversy Detection and Stance Analysis | Shiri Dori-Hacohen | Our existing work made strides in the emerging niche of controversy detection and analysis; we propose further work on automatic stance detection. |
| 168 | Using Contextual Information to Understand Searching and Browsing Behavior | Julia Kiseleva | Our results capture important aspects of context under the realistic conditions of different online search services, aiming to ensure that our scientific insights and solutions transfer to the operational settings of real world applications. |
| 169 | Transfer Learning for Information Retrieval | Pengfei Li | Transfer Learning for Information Retrieval |
| 170 | Enhancing Mathematics Information Retrieval | Martin Líška | Enhancing Mathematics Information Retrieval |
| 171 | Improving Search using Proximity-Based Statistics | Xiaolu Lu | Improving Search using Proximity-Based Statistics |
| 172 | Spoken Conversational Search: Information Retrieval over a Speech-only Communication Channel | Johanne R. Trippas | Spoken Conversational Search: Information Retrieval over a Speech-only Communication Channel |
| 173 | Finding Answers in Web Search | Evi Yulianti | In this research, we proposed to use a summarization technique through taking advantage of Community Question Answering (CQA) content. |
| 174 | Session details: Industry Track Preface | Hang Li, Jaime Teevan | Session details: Industry Track Preface |
| 175 | From Web Search Relevance to Vertical Search Relevance | Yi Chang | In this talk, the speaker will not only introduce state-of-the-art ranking algorithms for web search, but also cover the challenges to improve relevance of various vertical search engines: local search, shopping search, news search, etc. |
| 176 | Finding Money in the Haystack: Information Retrieval at Bloomberg | Jonathan J. Dorando, Konstantine Arkoudas, Parth Vasa, Gary Kazantsev, Gideon Mann | At Bloomberg, we have been addressing these problems over the past four years in the search and discoverability group, heavily leveraging the insights from the academic and open-source communities to apply to our problems. |
| 177 | If SIGIR had an Academic Track, What Would Be In It? | David Hawking | It used to be the case that very little industry research was presented at SIGIR. |
| 178 | WeChat Search & Headline: Sogou Joins Force with Tencent on Mobile Search | Chao Liu | This talk introduces how Tencent and Sogou join force on the battele of mobile search. |
| 179 | Structure, Personalization, Scale: A Deep Dive into LinkedIn Search | Asif Makhani | In this talk, we will discuss some of the unique challenges we’ve faced as we deliver highly personalized search over semi-structured data at massive scale. |
| 180 | Location in Search | Vanessa Murdock | In this talk we discuss gaps between current research on location, and industry advances in using location signals to improve search results. |
| 181 | Challenges and Opportunities in Online Evaluation of Search Engines | Pavel Serdyukov | Challenges and Opportunities in Online Evaluation of Search Engines |
| 182 | Lower Search Cost | Dou Shen | I will briefly explain the progress along these features, especially for the largest Chinese search engine – Baidu. |
| 183 | Practical Lessons for Gathering Quality Labels at Scale | Omar Alonso | In this paper we present a perspective for collecting high quality labels with an emphasis on practical problems and scalability. |
| 184 | Incremental Sampling of Query Logs | Ricardo Baeza-Yates | We introduce a simple technique to generate incremental query log samples that mimics well the original query distribution. |
| 185 | Where to Go on Your Next Trip?: Optimizing Travel Destinations Based on User Preferences | Julia Kiseleva, Melanie J.I. Mueller, Lucas Bernardi, Chad Davis, Ivan Kovacek, Mats Stafseng Einarsen, Jaap Kamps, Alexander Tuzhilin, Djoerd Hiemstra | We implement three methods and compare them to the current baseline in Booking.com: random, most popular, and Naive Bayes. |
| 186 | Bringing Order to the Job Market: Efficient Job Offer Categorization in E-Recruitment | Emmanuel Malherbe, Mario Cataldi, Andrea Ballatore | In order to support e-recruitment, this paper presents a dynamic, bottom-up method to automatically enrich and revise job categories. |
| 187 | Session details: Tutorials | Yoelle Maarek | The accepted tutorials include three fullday tutorials, and two morning-afternoon sequences. |
| 188 | Building and Using Models of Information Seeking, Search and Retrieval: Full Day Tutorial | Leif Azzopardi, Guido Zuccon | The latter sessions will be dedicated to building models that optimise particular objectives which drive how users make decisions, along with a how-to guide on model building, where we will describe different techniques (including analytical, graphical and computational) that can be used to generate hypotheses from such models. |
| 189 | Advanced Click Models and their Applications to IR: SIGIR 2015 Tutorial | Aleksandr Chuklin, Ilya Markov, Maarten de Rijke | The tutorial features a guest talk and a live demo where participants have a chance to build their own advanced click model. |
| 190 | An Introduction to Click Models for Web Search: SIGIR 2015 Tutorial | Aleksandr Chuklin, Ilya Markov, Maarten de Rijke | In this introductory tutorial we give an overview of click models for web search. |
| 191 | IR Evaluation: Modeling User Behavior for Measuring Effectiveness | Charles L.A. Clarke, Mark D. Smucker, Emine Yilmaz | The broad goal of the tutorial is to equip researchers with an understanding of modern approaches to IR evaluation, facilitating new research on this topic and improving evaluation methodology for emerging areas. |
| 192 | Information Retrieval with Verbose Queries | Manish Gupta, Michael Bendersky | In this tutorial, we aim to put together various research pieces of the puzzle, provide a comprehensive and structured overview of various proposed methods, and also list various application scenarios where effective verbose query processing can make a significant difference. |
| 193 | Revisiting the Foundations of IR: Timeless, Yet Timely | Paul B. Kantor | The purpose of this tutorial is to survey those roots, and their relation to the contemporary fruits on the tree of information retrieval, and to separate, as much as is possible in an era of increasing commercial secrecy about methods, the problems to be solved, the algorithms for solving them, and the heuristics that are the bread and butter of a working operation. |
| 194 | IR Evaluation: Designing an End-to-End Offline Evaluation Pipeline | Jin Young Kim, Emine Yilmaz | The tutorial will give an overview of the state of the art methods, techniques, and metrics necessary for each stage of evaluation process. |
| 195 | Music Retrieval and Recommendation: A Tutorial Overview | Peter Knees, Markus Schedl | In this tutorial, we give an introduction to the field of and state of the art in music information retrieval (MIR). |
| 196 | Exploiting Wikipedia for Information Retrieval Tasks | Bracha Shapira, Nir Ofek, Victor Makarenkov | Wikipedia – the online encyclopedia – has long been used as a source of information for researchers, as well as being a subject of research itself. |
| 197 | Session details: Workshops | Fernando Diaz, Diane Kelly | This year’s workshops include new explorations of established topics such as temporal information retrieval, personalization, and question answering. |
| 198 | Web Question Answering: Beyond Factoids: SIGIR 2015 Workshop | Eugene Agichtein, David Carmel, Charles L.A. Clarke, Praveen Paritosh, Dan Pelleg, Idan Szpektor | Web Question Answering: Beyond Factoids: SIGIR 2015 Workshop |
| 199 | Graph Search and Beyond: SIGIR 2015 Workshop Summary | Omar Alonso, Marti A. Hearst, Jaap Kamps | The workshop attracted a range of researchers working on this and related topics, and made concrete progress working together on one of the greatest challenges in the years to come. |
| 200 | SIGIR 2015 Workshop on Reproducibility, Inexplicability, and Generalizability of Results (RIGOR) | Jaime Arguello, Fernando Diaz, Jimmy Lin, Andrew Trotman | SIGIR 2015 Workshop on Reproducibility, Inexplicability, and Generalizability of Results (RIGOR) |
| 201 | SIGIR 2015 Workshop on Temporal, Social and Spatially-aware Information Access (#TAIA2015) | Klaus Berberich, James Caverlee, Miles Efron, Claudia Hauff, Vanessa Murdock, Milad Shokouhi, Bart Thomee | In this workshop we aim to bring together practitioners and researchers to discuss their recent breakthroughs and the challenges with addressing spatial and temporal information access, both from the algorithmic and the architectural perspectives. |
| 202 | NeuroIR 2015: Neuro-Physiological Methods in IR Research | Jacek Gwizdka, Joemon Jose, Javed Mostafa, Max Wilson | This Tutorial+Workshop will discuss opportunities and challenges involved in using neuro-physiological tools/techniques (such as fMRI, fNIRS, EEG, eye-tracking, GSR, HR, and facial expressions) and theories in information retrieval. |
| 203 | SPS’15: 2015 International Workshop on Social Personalization & Search | Christoph Trattner, Denis Parra, Peter Brusilovsky, Leandro Marinho | SPS’15: 2015 International Workshop on Social Personalization & Search |
| 204 | Privacy-Preserving IR 2015: When Information Retrieval Meets Privacy and Security | Hui Yang, Ian Soboroff | We propose this privacy-preserving IR workshop to connect the two disciplines of information retrieval and information privacy and security. |