Supervised Search Result Diversification via Subtopic Attention
暂无分享,去创建一个
Ji-Rong Wen | Ming Yue | Jian-Yun Nie | Zhicheng Dou | Wayne Xin Zhao | Zhengbao Jiang | Jian-Yun Nie | Zhengbao Jiang | Ji-Rong Wen | Zhicheng Dou | Ming Yue
[1] Tie-Yan Liu,et al. Listwise approach to learning to rank: theory and algorithm , 2008, ICML '08.
[2] Enrique Alfonseca,et al. Generalized syntactic and semantic models of query reformulation , 2010, SIGIR.
[3] Farzin Maghoul,et al. Query clustering using click-through graph , 2009, WWW '09.
[4] Ismail Sengör Altingövde,et al. Scalable and Efficient Web Search Result Diversification , 2016, ACM Trans. Web.
[5] Charles L. A. Clarke,et al. An Effectiveness Measure for Ambiguous and Underspecified Queries , 2009, ICTIR.
[6] Tetsuya Sakai,et al. Evaluating Search Result Diversity using Intent Hierarchies , 2016, SIGIR.
[7] Xueqi Cheng,et al. Learning for search result diversification , 2014, SIGIR.
[8] Jade Goldstein-Stewart,et al. The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries , 1998, SIGIR Forum.
[9] Yoshua Bengio,et al. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling , 2014, ArXiv.
[10] Fuji Ren,et al. Search Result Diversification via Filling Up Multiple Knapsacks , 2014, CIKM.
[11] Christopher D. Manning,et al. Effective Approaches to Attention-based Neural Machine Translation , 2015, EMNLP.
[12] Olfa Nasraoui,et al. Mining search engine query logs for query recommendation , 2006, WWW '06.
[13] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[14] Tie-Yan Liu,et al. Learning to rank for information retrieval , 2009, SIGIR.
[15] Charles L. A. Clarke,et al. Novelty and diversity in information retrieval evaluation , 2008, SIGIR '08.
[16] Olivier Chapelle,et al. Expected reciprocal rank for graded relevance , 2009, CIKM.
[17] W. Bruce Croft,et al. Diversity by proportionality: an election-based approach to search result diversification , 2012, SIGIR '12.
[18] Craig MacDonald,et al. Explicit Search Result Diversification through Sub-queries , 2010, ECIR.
[19] Sreenivas Gollapudi,et al. Diversifying search results , 2009, WSDM '09.
[20] Ricardo A. Baeza-Yates,et al. Query Recommendation Using Query Logs in Search Engines , 2004, EDBT Workshops.
[21] Ben Carterette,et al. An analysis of NP-completeness in novelty and diversity ranking , 2009, Information Retrieval.
[22] Craig MacDonald,et al. Exploiting query reformulations for web search result diversification , 2010, WWW '10.
[23] Yiqun Liu,et al. Overview of the NTCIR-10 INTENT-2 Task , 2013, NTCIR.
[24] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[25] W. Bruce Croft,et al. Term level search result diversification , 2013, SIGIR.
[26] Quoc V. Le,et al. Distributed Representations of Sentences and Documents , 2014, ICML.
[27] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[28] Tetsuya Sakai,et al. Search Result Diversification Based on Hierarchical Intents , 2015, CIKM.
[29] Danqi Chen,et al. Reasoning With Neural Tensor Networks for Knowledge Base Completion , 2013, NIPS.
[30] Larry P. Heck,et al. Learning deep structured semantic models for web search using clickthrough data , 2013, CIKM.
[31] Jade Goldstein-Stewart,et al. The use of MMR, diversity-based reranking for reordering documents and producing summaries , 1998, SIGIR '98.
[32] Tetsuya Sakai,et al. Evaluating diversified search results using per-intent graded relevance , 2011, SIGIR.
[33] Xueqi Cheng,et al. Modeling Document Novelty with Neural Tensor Network for Search Result Diversification , 2016, SIGIR.
[34] Evaggelia Pitoura,et al. Search result diversification , 2010, SGMD.
[35] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[36] Jun Wang,et al. Top-k Retrieval Using Facility Location Analysis , 2012, ECIR.
[37] Alex Graves,et al. Recurrent Models of Visual Attention , 2014, NIPS.
[38] Yiqun Liu,et al. Overview of the NTCIR-11 IMine Task , 2014, NTCIR.
[39] Alessandro Moschitti,et al. Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks , 2015, SIGIR.
[40] J. Marden. Analyzing and Modeling Rank Data , 1996 .
[41] Thorsten Joachims,et al. Predicting diverse subsets using structural SVMs , 2008, ICML '08.
[42] Xueqi Cheng,et al. Learning Maximal Marginal Relevance Model via Directly Optimizing Diversity Evaluation Measures , 2015, SIGIR.
[43] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..