Guang Qiu
ABSTRACT
Query ambiguity prevents existing retrieval systems from returning reasonable results for every query. As there is already lots of work done on resolving ambiguity, vague queries could be handled using corresponding approaches separately if they can be identified in advance. Quantification of the degree of (lack of) ambiguity laysthe groundwork for the identification. In this poster, we propose such a measure using query topics based on the topic structure selected from the Open Directory Project (ODP) taxonomy. We introduce clarity score to quantify the lack of ambiguity with respect to data sets constructed from the TREC collections and the rank correlation test results demonstrate a strong positive association between the clarity scores and retrieval precisions for queries.
- S. Cronen-Townsend and W. B. Croft. Quantifying query ambiguity. In Proceedings of Human Language Technology, pages 94--98, 2002. Google Scholar
Digital Library
- M. Sanderson and K. van Rijsbergen. The impact on retrieval effectiveness of skewed frequency distributions. ACM Transactions on Information Systems, 17(4):440--465, 1999. Google ScholarDigital Library
- H. Schutze and J. Pederson. Information retrieval based on word senses. In Proceedings of the 4th Annual Symposium on Document Analysis and Information Retrieval, pages 161--175, 1995.Google Scholar
- I. Soboroff. Overview of the trec 2004 novelty track. In Proceedings of the Thirteenth Text REtrieval Conference (TREC 2004), NIST Special Publication 500--261, 2004.Google Scholar
- E. Voorhees. Overview of the trec 2003 robust retrieval track. In Proceedings of the Twelfth Text REtrieval Conference Proceedings (TREC 2003), NIST Special Publication 500--255, 2003.Google Scholar
Index Terms
- Quantify query ambiguity using ODP metadata
Recommendations
Predicting query performance
SIGIR '02: Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrievalWe develop a method for predicting query performance by computing the relative entropy between a query language model and the corresponding collection language model. The resulting clarity score measures the coherence of the language usage in documents ...
TAPHSIR: towards AnaPHoric ambiguity detection and ReSolution in requirements
ESEC/FSE 2022: Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software EngineeringWe introduce TAPHSIR – a tool for anaphoric ambiguity detection and anaphora resolution in requirements. TAPHSIR facilities reviewing the use of pronouns in a requirements specification and revising those pronouns that can lead to misunderstandings ...
Quantifying query ambiguity
HLT '02: Proceedings of the second international conference on Human Language Technology ResearchWe develop a measure of a query with respect to a collection of documents with the aim of quantifying the query's ambiguity with respect to those documents. This measure, the clarity score, is the relative entropy between a query language model and the ...
Comments