NDLI: A unified model for metasearch and the efficient evaluation of retrieval systems via the hedge algorithm

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A unified model for metasearch and the efficient evaluation of retrieval systems via the hedge algorithm

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A unified model for metasearch and the efficient evaluation of retrieval systems via the hedge algorithm

Content Provider	ACM Digital Library
Author	Pavlu, Virgiliu Aslam, Javed A. Savell, Robert
Abstract	We present a unified framework for simultaneously solving both the pooling problem (the construction of efficient document pools for the evaluation of retrieval systems) and metasearch (the fusion of ranked lists returned by retrieval systems in order to increase performance). The implementation is based on the Hedge algorithm for online learning, which has the advantage of convergence to bounded error rates approaching the performance of the best linear combination of the underlying systems. The choice of a loss function closely related to the average precision measure of system performance ensures that the judged document set performs well, both in constructing a metasearch list and as a pool for the accurate evaluation of retrieval systems. Our experimental results on TREC data demonstrate excellent performance in all measures---evaluation of systems, retrieval of relevant documents, and generation of metasearch lists.
Starting Page	393
Ending Page	394
Page Count	2
File Format	PDF
ISBN	1581136463
DOI	10.1145/860435.860517
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2003-07-28
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Retrieval systems Metasearch Pooling
Content Type	Text
Resource Type	Article

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