An adaptable connectionist text-retrieval system with relevance feedback
dc.contributor.author | Sheedvash, Sassan, author | |
dc.contributor.author | Srinivasan, S. (Srini), author | |
dc.contributor.author | Salazar, Jaime, author | |
dc.contributor.author | Azimi-Sadjadi, Mahmood R., author | |
dc.contributor.author | IEEE, publisher | |
dc.date.accessioned | 2007-01-03T04:49:01Z | |
dc.date.available | 2007-01-03T04:49:01Z | |
dc.date.issued | 2007 | |
dc.description.abstract | This paper introduces a new connectionist network for certain domain-specific text-retrieval and search applications with expert end users. A new model reference adaptive system is proposed that involves three learning phases. Initial model-reference learning is first performed based upon an ensemble set of input-output of an initial reference model. Model-reference following is needed in dynamic environments where documents are added, deleted, or updated. Relevance feedback learning from multiple expert users then optimally maps the original query using either a score-based or a click-through selection process. The learning can be implemented, in regression or classification modes, using a three-layer network. The first layer is an adaptable layer that performs mapping from query domain to document space. The second and third layers perform document-to-term mapping, search/retrieval, and scoring tasks. The learning algorithms are thoroughly tested on a domain-specific text database that encompasses a wide range of Hewlett Packard (HP) products and for a large number of most commonly used single- and multiterm queries. | |
dc.description.sponsorship | This work was supported by the Hewlett Packard, Boise, ID management and business teams under Contract 50B000553. | |
dc.format.medium | born digital | |
dc.format.medium | articles | |
dc.identifier.bibliographicCitation | Azimi-Sadjadi, M. R., et al., An Adaptable Connectionist Text-Retrieval System with Relevance Feedback, IEEE Transactions on Neural Networks 18, no. 6 (November 2007): 1597-1613. | |
dc.identifier.uri | http://hdl.handle.net/10217/931 | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | Colorado State University. Libraries | |
dc.relation.ispartof | Faculty Publications | |
dc.rights | ©2007 IEEE. | |
dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
dc.subject | query mapping | |
dc.subject | learning algorithms | |
dc.subject | connectionist networks | |
dc.subject | relevance feedback | |
dc.subject | text retrieval | |
dc.title | An adaptable connectionist text-retrieval system with relevance feedback | |
dc.type | Text |
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