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1
Relevance Feedback based on Constrained Clustering: FDU at TREC 09
In: DTIC (2009)
Abstract: We introduce our participation of the TREC Relevance Feedback(RF) TRACK in 2009. The RF09 TRACK is focused on the explicit relevant feedback, where a few relevant and irrelevant documents are available to each query. Our system is implemented under the framework of probabilistic language model. We apply the constrained clustering on the top returned documents and extract the expanded words to reform the query. We also extract the named entities from the explicit relevant documents to expand the query. The experiment was conducted on the ClueWeb09 TREC Category B, which is a new and huge test collection for the TREC TRACKs. The evaluation result shows the performance of the constrained clustering. ; Presented at the Text REtrieval Conference (TREC 2009, 18th) held in Gaithersburg, Maryland on 17-20 November 2009. Published in the Proceedings of the Text REtrieval Conference (TREC 2009, 18th), 2009. The conference was co-sponsored by the National Institute of Standards and Technology (NIST), the Defense Advanced Research Projects Agency (DARPA), and the Advanced Research and Development Activity (ARDA). The original document contains color images.
Keyword: *CLUSTERING; *FEEDBACK; *INFORMATION RETRIEVAL; *INFORMATION SCIENCES; *INTERNET; *RF(RELEVANCE FEEDBACK); CHINA; COLLECTION; Computer Programming and Software; CONSTRAINED CLUSTERING; Equipment and Methods; EXPANSION; FOREIGN REPORTS; Information Science; INTERNET BROWSERS; LANGUAGE; Linguistics; MATHEMATICAL MODELS; PROBABILITY; QUERIES(INFORMATION SCIENCES); RELEVANCE(INFORMATION SCIENCES); REPRINTS; SOCIAL COMMUNICATION; SYMPOSIA; TEST AND EVALUATION; Test Facilities; WORDS(LANGUAGE)
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA517715
http://www.dtic.mil/docs/citations/ADA517715
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2
BIT at TREC 2009 Faceted Blog Distillation Task
In: DTIC (2009)
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3
POSTECH at TREC 2009 Blog Track: Top Stories Identification
In: DTIC (2009)
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4
PRIS at 2009 Relevance Feedback track: Experiments in Language Model for Relevance Feedback
In: DTIC (2009)
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