Using key phrases as new queries in building relevance judgements

2.50
Hdl Handle:
http://hdl.handle.net/2436/620408
Title:
Using key phrases as new queries in building relevance judgements
Authors:
Makary, Mireille; Oakes, Michael; Yamout, Fadi
Abstract:
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.
Publisher:
CEUR - workshop proceedings
Journal:
Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", Potsdam, Germany, 2016, pp 175-176
Issue Date:
Sep-2017
URI:
http://hdl.handle.net/2436/620408
Additional Links:
http://ceur-ws.org/Vol-1670/
Type:
Meetings and Proceedings
Language:
en
ISSN:
1613-0073
Appears in Collections:
FOSS

Full metadata record

DC FieldValue Language
dc.contributor.authorMakary, Mireilleen
dc.contributor.authorOakes, Michaelen
dc.contributor.authorYamout, Fadien
dc.date.accessioned2017-03-09T10:49:27Z-
dc.date.available2017-03-09T10:49:27Z-
dc.date.issued2017-09-
dc.identifier.issn1613-0073en
dc.identifier.urihttp://hdl.handle.net/2436/620408-
dc.description.abstractWe 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.en
dc.language.isoenen
dc.publisherCEUR - workshop proceedingsen
dc.relation.urlhttp://ceur-ws.org/Vol-1670/en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectInformation Retrievalen
dc.subjectKey Phrasesen
dc.subjectTest Collectionsen
dc.titleUsing key phrases as new queries in building relevance judgementsen
dc.typeMeetings and Proceedingsen
dc.identifier.journalProceedings of the Conference "Lernen, Wissen, Daten, Analysen", Potsdam, Germany, 2016, pp 175-176en
dc.date.accepted2017-07-
rioxxterms.funderInternalen
rioxxterms.identifier.projectUoW090317MOen
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/CC BY-NC-ND 4.0en
rioxxterms.licenseref.startdate2017-03-09en
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