Wei Zheng
ABSTRACT
Search result diversification aims to return a list of diversified relevant documents in order to satisfy different user information needs. Most of the efforts focused on Web Search, and few studies have considered another important search domain, i.e., enterprise search. Unlike Web search, enterprise search deals with both unstructured and structured data. In this paper, we propose to integrate the structured and unstructured data to discover meaningful query subtopics in search result diversification. Experimental results show that integrating structured and unstructured information allows us to discover high quality query, which are effective in diversifying the retrieval results.
- R. Agrawal, S. Gollapudi, A. Halverson, and S. Ieong. Diversifying Search Results. In WSDM, 2009. Google Scholar
Digital Library
- B. Carterette and P. Chandar. Probabilistic Models of Novel Document Rankings for Faceted Topic Retrieval. In CIKM, 2009. Google ScholarDigital Library
- Z. Chen and T. Li. Addressing diverse user preferences in sql-query-result navigation. In Proceedings of SIGMOD'07, 2007. Google ScholarDigital Library
- C. L. A. Clarke, N. Craswell, and I. Soboroff. Overview of the TREC 2009 Web Track. In Proceedings of TREC'09, 2009.Google Scholar
- E. Demidova, P. Fankhauser, X. Zhou, and W. Nejdl. Divq: Diversification for keyword search over structured databases. In Proceedings of SIGIR'10, 2010. Google ScholarDigital Library
- Z. Dou, S. Hu, K. Chen, R. Song, and J. R. Wen. Multi-dimensional search result diversification. In Proceedings of WSDM'11, 2011. Google ScholarDigital Library
- H. Fang and C. Zhai. Semantic Term Matching in Axiomatic Approaches to Information Retrieval. In SIGIR, 2006. Google ScholarDigital Library
- S. Feldman and C. Sherman. The High Cost of Not Finding Information. In Technical Report No. 29127, IDC, 2003.Google Scholar
- S. Geva. Gpx - gardens point xml ir at inex 2006. In Proceedings of INEX'06, 2006.Google Scholar
- C. Hauff and D. Hiemstra. University of Twente @ TREC 2009: Indexing half a billion web pages. In Proceedings of TREC'09, 2009.Google Scholar
- T. Hofmann. Probabilistic latent semantic analysis. In Proceedings of UAI'99, 1999. Google ScholarDigital Library
- P. Lubell-Doughtie and K. Hofmann. Improving result diversity using probabilistic latent semantic analysis. In Proceedings of DIR'11, 2011.Google Scholar
- R. L. T. Santos, C. Macdonald, and I. Ounis. Exploiting Query Reformulations for Web Search Result Diversification. In WWW, 2010. Google ScholarDigital Library
- R. L. T. Santos, C. Macdonald, and I. Ounis. Selectively Diversifying Web Search Results. In CIKM, 2010. Google ScholarDigital Library
- C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. In Proceedings of SIGIR'01, 2001. Google ScholarDigital Library
- W. Zheng, X. Wang, H. Fang, and H. Cheng. An exploration of pattern-based subtopic modeling for search result diversification. In Proceedings of JCDL'11, 2011. Google ScholarDigital Library
Index Terms
- Search result diversification for enterprise data
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