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- 94 creator jagadeesh-jagarlamudi.
- 94 creator jianfeng-gao.
- 94 type InProceedings.
- 94 label "Modeling Click-through based Word-pairs for Web Search".
- 94 sameAs 94.
- 94 abstract "Statistical translation models and latent semantic analysis (LSA) are two effective approaches to exploiting 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 PairModel, 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 can jointly model a bilingual query-document collection. This model maps queries and documents in multiple languages into a lower dimensional semantic sub-space. Experimental results on web search task show that they significantly out-perform the state-of-the-art baseline models, and the best result is obtained by interpolating PairModel and BPTM.".
- 94 hasAuthorList authorList.
- 94 isPartOf proceedings.
- 94 isPartOf proceedings.
- 94 keyword "Clickthrough Data".
- 94 keyword "Latent Semantic Analysis".
- 94 keyword "Multilingual IR".
- 94 keyword "Topic Models".
- 94 keyword "Translation Model".
- 94 keyword "Web Search".
- 94 keyword "Word Pairs".
- 94 title "Modeling Click-through based Word-pairs for Web Search".