Contextual keyword extraction by building sentences with crowdsourcing

Cited 1 time in webofscience Cited 0 time in scopus
  • Hit : 441
  • Download : 43
DC FieldValueLanguage
dc.contributor.authorHong, Soon Gillko
dc.contributor.authorShin, Sunghoko
dc.contributor.authorYi, Mun Yongko
dc.date.accessioned2014-09-04T08:46:51Z-
dc.date.available2014-09-04T08:46:51Z-
dc.date.created2014-03-25-
dc.date.created2014-03-25-
dc.date.issued2014-01-
dc.identifier.citationMULTIMEDIA TOOLS AND APPLICATIONS, v.68, no.2, pp.401 - 412-
dc.identifier.issn1380-7501-
dc.identifier.urihttp://hdl.handle.net/10203/190194-
dc.description.abstractAutomatic keyword extraction from documents has long been used and proven its usefulness in various areas. Crowdsourced tagging for multimedia resources has emerged and looks promising to a certain extent. Automatic approaches for unstructured data, automatic keyword extraction and crowdsourced tagging are efficient but they all suffer from the lack of contextual understanding. In this paper, we propose a new model of extracting key contextual terms from unstructured data, especially from documents, with crowdsourcing. The model consists of four sequential processes: (1) term selection by frequency, (2) sentence building, (3) revised term selection reflecting the newly built sentences, and (4) sentence voting. Online workers read only a fraction of a document and participated in sentence building and sentence voting processes, and key sentences were generated as a result. We compared the generated sentences to the keywords entered by the author and to the sentences generated by offline workers who read the whole document. The results support the idea that sentence building process can help selecting terms with more contextual meaning, closing the gap between keywords from automated approaches and contextual understanding required by humans.-
dc.languageEnglish-
dc.publisherSPRINGER-
dc.titleContextual keyword extraction by building sentences with crowdsourcing-
dc.typeArticle-
dc.identifier.wosid000331083400014-
dc.identifier.scopusid2-s2.0-84895064515-
dc.type.rimsART-
dc.citation.volume68-
dc.citation.issue2-
dc.citation.beginningpage401-
dc.citation.endingpage412-
dc.citation.publicationnameMULTIMEDIA TOOLS AND APPLICATIONS-
dc.identifier.doi10.1007/s11042-012-1338-z-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorYi, Mun Yong-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorCrowdsourcing-
dc.subject.keywordAuthorKeyword extraction-
dc.subject.keywordAuthorDocument summary-
dc.subject.keywordAuthorContent extraction-
dc.subject.keywordAuthorSentence building-
dc.subject.keywordAuthorContextual term extraction-
Appears in Collection
IE-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 1 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0