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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 Modeling Click-through based Word-pairs for Web Search Jagadeesh Jagarlamudi; Jianfeng Gao In: http://www2012.wwwconference.org/proceedings/companion/p537.pdf (2012) BASE Show details 2 A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval Min Zhang; Xingyao Ye In: http://www.thuir.cn/group/~mzhang/publications/SIGIR08-zhang.pdf (2008) BASE Show details 3 Modeling Click-through based Word-pairs for Web Search Jagadeesh Jagarlamudi; Jianfeng Gao In: http://www.umiacs.umd.edu/%7Ejags/pdfs/jags12PairModel.pdf BASE Show details 4 Modeling Click-through based Word-pairs for Web Search Jagadeesh Jagarlamudi; Jianfeng Gao In: http://www.research.microsoft.com/%7Ejfgao/paper/2012-papers/wpp094-Jagarlamudi.pdf Abstract: Statistical translation models and latent semantic analysis (LSA) are two effective approaches to exploit click-through data for web search ranking. This paper presents two document ranking models that combine both approaches by explicitly modeling word-pairs. The first model, called Pair-Model, is a monolingual ranking model based on word pairs that are derived from click-through data. It maps queries and documents into a concept space spanned by these word pairs. The second model, called Bilingual Paired Topic Model (BPTM), uses bilingual word pairs and jointly models a bilingual query-document collection. This model maps queries and documents in multiple languages into a lower dimensional semantic subspace. Experimental results on web search task show that they significantly outperform the state-of-the-art baseline models, and the best result is obtained by interpolating PairModel and BPTM. Keyword: Algorithms; Experimentation Keywords Clickthrough Data; General Terms Learning; Latent Semantic Analysis; Multilingual IR; Topic Models; Translation Model; Web Search URL: http://www.research.microsoft.com/%7Ejfgao/paper/2012-papers/wpp094-Jagarlamudi.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.259.6204 BASE Hide details 5 57 Text Summarization Based on Genetic Programming Pooya Khosraviyan Dehkordi; Dr. Farshad Kumarci; Dr. Hamid Khosravi In: http://ijcir.org/volume3-number1/issue 57-64.pdf BASE Show details 6 2008. Multi-document summarization using cluster-based link analysis Xiaojun Wan; Jianwu Yang In: http://www.cs.fiu.edu/%7Elli003/Sum/SIGIR/2008/2.pdf BASE Show details 7 7Integrating Generative and Discriminative Character-Based Models for Chinese Word Segmentation In: http://www.nlpr.ia.ac.cn/cip/ZongPublications/2012/2012.06+ACM+TALIP+K.Wang.pdf BASE Show details

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