Matthew W. Bilotti
Jamie Callan
ABSTRACT
Bag-of-words retrieval is popular among Question Answering (QA) system developers, but it does not support constraint checking and ranking on the linguistic and semantic information of interest to the QA system. We present anapproach to retrieval for QA, applying structured retrieval techniques to the types of text annotations that QA systems use. We demonstrate that the structured approach can retrieve more relevant results, more highly ranked, compared with bag-of-words, on a sentence retrieval task. We also characterize the extent to which structured retrieval effectiveness depends on the quality of the annotations.
- D. Bikel, et al. An algorithm that learns what's in a name. ML, 34(1-3):211--231, 1999. Google Scholar
Digital Library
- M. Bilotti, et al. What works better for question answering: Stemming or morphological query expansion? In Proc. of IR4QA at SIGIR, 2004.Google Scholar
- D. Carmel, et al. Searching XML documents via XML fragments. In Proc. of SIGIR, 2003. Google ScholarDigital Library
- H. Cui, et al. Question answering passage retrieval using dependency relations. In Proc. of SIGIR, 2005. Google ScholarDigital Library
- D. Graff. The AQUAINT Corpus of English News Text. LDC, 2002. Cat. No. LDC2002T31.Google Scholar
- S. Harabagiu, et al. Employing two question answering systems in TREC-2005. In Proc. of TREC-14, 2005.Google Scholar
- P. Kingsbury, et al. Adding semantic annotation to the penn treebank. In Proc. of HLT, 2002.Google Scholar
- C. Lin and E. Hovy. The automated acquisition of topic signatures for text summarization. In Proc. of COLING, 2000. Google ScholarDigital Library
- J. Lin and B. Katz. Building a reusable test collection for question answering. JASIST, 57(7):851--861, 2006. Google ScholarDigital Library
- M. Marcus, et al. Building a large annotated corpus of english: the penn treebank. CL, 19(2):313--330, 1993. Google ScholarDigital Library
- M. Montague and J. Aslam. Relevance score normalization for metasearch. In Proc. of CIKM, 2001. Google ScholarDigital Library
- P. Ogilvie and J. Callan. Combining document representations for known-item search. In Proc. of SIGIR, 2003. Google ScholarDigital Library
- S. Pradhan, et al. Shallow semantic parsing using support vector machines. In Proc. of HLT, 2004.Google Scholar
- J. Prager, et al. Question-answering by predictive annotation. In Proc. of SIGIR, 2000. Google ScholarDigital Library
- T. Rajashekar and W. B. Croft. Combining automatic and manual index representations in probabilistic retrieval. JASIS, 46(4):272--283, 1995. Google ScholarDigital Library
- J. Reynar and A. Ratnaparkhi. A maximum entropy approach to identifying sentence boundaries. In Proc. of ANLP, 1997. Google ScholarDigital Library
- J. Shaw and E. Fox. Combination of multiple searches. In Proc. of TREC-3, 1994.Google Scholar
- T. Strohman, et al. Indri: A language model-based search engine for complex queries. In Proc. of ICIA, 2005.Google Scholar
- S. Tellex, et al. Quantitative evaluation of passage retrieval algorithms for question answering. In Proc. of SIGIR, 2003. Google ScholarDigital Library
- H. Turtle and W. Croft. Evaluation of an inference network-based retrieval model. ACM TOIS, 9(3):187--222, 1991. Google ScholarDigital Library
- E. Voorhees, et al. The collection fusion problem. In Proc. of TREC-3, 1994.Google Scholar
- C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. In Proc. of SIGIR, 2001. Google ScholarDigital Library
Index Terms
- Structured retrieval for question answering
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