Using key phrases as new queries in building relevance judgements automatically
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Issue Date
2016-09-30
Metadata
Show full item recordAbstract
We describe a new technique for building a relevance judgment list (qrels) for TREC test collections with no human intervention. For each TREC topic, a set of new queries is automatically generated from key phrases extract-ed from the top k documents retrieved from 12 different Terrier weighting models when the initial TREC topic is submitted. We assign a score to each key phrase based on its similarity to the original TREC topic. The key phrases with the highest scores become the new queries for a second search, this time using the Terrier BM25 weighting model. The union of the documents retrieved forms the automatically-build set of qrels.Citation
Makary, M., Oakes, M., Yamout, F. (2016) 'Using key phrases as new queries in building relevance judgements automatically', Lernen,Wissen, Daten, Analysen (LWDA) Conference Proceedings, LWDA'16, September 12-14, Potsdam, Germany: CEUR - workshop proceedings, 1670, pp. 175-176.Publisher
CEUR - workshop proceedingsJournal
Proceedings of the Conference "Lernen, Wissen, Daten, Analysen"Additional Links
http://ceur-ws.org/Vol-1670/Type
Conference contributionLanguage
enISSN
1613-0073Collections
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- Creative Commons
Except where otherwise noted, this item's license is described as https://creativecommons.org/CC BY-NC-ND 4.0