Topic-enhanced knowledge-aware retrieval model for diverse relevance estimation
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Yiqun Liu | Shaoping Ma | Jiaxin Mao | Weizhi Ma | Xiuqiang He | Min Zhang | Zhaowei Wang | Xiangsheng Li
[1] Yiqun Liu,et al. Understanding Reading Attention Distribution during Relevance Judgement , 2018, CIKM.
[2] Larry P. Heck,et al. Learning deep structured semantic models for web search using clickthrough data , 2013, CIKM.
[3] Carlos Valle,et al. Ad-hoc Information Retrieval based on Boosted Latent Dirichlet Allocated Topics , 2018, 2018 37th International Conference of the Chilean Computer Science Society (SCCC).
[4] W. Bruce Croft,et al. LDA-based document models for ad-hoc retrieval , 2006, SIGIR.
[5] Hang Li,et al. Convolutional Neural Network Architectures for Matching Natural Language Sentences , 2014, NIPS.
[6] Thore Graepel,et al. Kernel Topic Models , 2011, AISTATS.
[7] Tefko Saracevic. Relevance: A review of the literature and a framework for thinking on the notion in information science. Part III: Behavior and effects of relevance , 2007 .
[8] Charles A. Sutton,et al. Autoencoding Variational Inference For Topic Models , 2017, ICLR.
[9] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[10] Raymond Y. K. Lau,et al. Bootstrapping Social Emotion Classification with Semantically Rich Hybrid Neural Networks , 2017, IEEE Transactions on Affective Computing.
[11] CHENGXIANG ZHAI,et al. A study of smoothing methods for language models applied to information retrieval , 2004, TOIS.
[12] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[13] Benjamin Piwowarski,et al. A user browsing model to predict search engine click data from past observations. , 2008, SIGIR '08.
[14] Tefko Saracevic,et al. The Notion of Relevance in Information Science: Everybody knows what relevance is. But, what is it really? , 2016, The Notion of Relevance in Information Science.
[15] Andrew McCallum,et al. Optimizing Semantic Coherence in Topic Models , 2011, EMNLP.
[16] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[17] Jason Weston,et al. Translating Embeddings for Modeling Multi-relational Data , 2013, NIPS.
[18] Yiqun Liu,et al. Incorporating Non-sequential Behavior into Click Models , 2015, SIGIR.
[19] Brian D. Davison,et al. Empirical study of topic modeling in Twitter , 2010, SOMA '10.
[20] Xiangji Huang,et al. A Simple Enhancement for Ad-hoc Information Retrieval via Topic Modelling , 2016, SIGIR.
[21] Bhaskar Mitra,et al. An Introduction to Neural Information Retrieval , 2018, Found. Trends Inf. Retr..
[22] Yiqun Liu,et al. Teach Machine How to Read: Reading Behavior Inspired Relevance Estimation , 2019, SIGIR.
[23] Xueqi Cheng,et al. A Deep Investigation of Deep IR Models , 2017, ArXiv.
[24] SaracevicTefko. Relevance: A review of the literature and a framework for thinking on the notion in information science. Part III: Behavior and effects of relevance , 2007 .
[25] Stefano Mizzaro,et al. How many relevances in information retrieval? , 1998, Interact. Comput..
[26] Zhiyuan Liu,et al. End-to-End Neural Ad-hoc Ranking with Kernel Pooling , 2017, SIGIR.
[27] Zhiyuan Liu,et al. Entity-Duet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrieval , 2018, ACL.
[28] Yiqun Liu,et al. TianGong-ST: A New Dataset with Large-scale Refined Real-world Web Search Sessions , 2019, CIKM.
[29] Tie-Yan Liu,et al. Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling , 2018, SIGIR.
[30] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[31] W. Bruce Croft,et al. A Deep Look into Neural Ranking Models for Information Retrieval , 2019, Inf. Process. Manag..
[32] Tim Salimans,et al. Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression , 2012, ArXiv.
[33] Phil Blunsom,et al. Discovering Discrete Latent Topics with Neural Variational Inference , 2017, ICML.
[34] Stephen E. Robertson,et al. Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval , 1994, SIGIR '94.
[35] Peng Zhang,et al. XLore: A Large-scale English-Chinese Bilingual Knowledge Graph , 2013, SEMWEB.
[36] Jiaul H. Paik. A novel TF-IDF weighting scheme for effective ranking , 2013, SIGIR.
[37] Krisztian Balog,et al. Entity Linking in Queries: Efficiency vs. Effectiveness , 2017, ECIR.
[38] Yong Yu,et al. Identification of ambiguous queries in web search , 2009, Inf. Process. Manag..
[39] Jure Leskovec,et al. node2vec: Scalable Feature Learning for Networks , 2016, KDD.
[40] Thomas Hofmann,et al. Probabilistic Latent Semantic Indexing , 1999, SIGIR Forum.
[41] Xueqi Cheng,et al. Text Matching as Image Recognition , 2016, AAAI.
[42] M. de Rijke,et al. Click Models for Web Search , 2015, Click Models for Web Search.
[43] Nicholas J. Belkin. People, Interacting with Information1 , 2016, SIGF.