Every paper, ordered by impact or potential impact. About SIGIR 2015
| ID | Paper | Authors | Source | Date |
|---|---|---|---|---|
| 1 | Image-Based Recommendations On Styles And Substitutes IF:9 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: 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. | Julian McAuley; Christopher Targett; Qinfeng Shi et al. | sigir | 2015-07-29 |
| 2 | Learning To Rank Short Text Pairs With Convolutional Deep Neural Networks IF:8 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: 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. | Aliaksei Severyn; Alessandro Moschitti; | sigir | 2015-07-29 |
| 3 | Twitter Sentiment Analysis With Deep Convolutional Neural Networks IF:7 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: 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. | Aliaksei Severyn; Alessandro Moschitti; | sigir | 2015-07-29 |
| 4 | Monolingual And Cross-Lingual Information Retrieval Models Based On (Bilingual) Word Embeddings IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: 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. | Ivan Vulić; Marie-Francine Moens; | sigir | 2015-07-29 |
| 5 | Learning Hierarchical Representation Model For NextBasket Recommendation IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To tackle the above problems, in this paper, we introduce a novel recommendation approach, namely hierarchical representation model (HRM). | Pengfei Wang; Jiafeng Guo; Yanyan Lan et al. | sigir | 2015-07-29 |
This page lists the papers of ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2015), ordered by impact or potential impact.