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dc.contributor.authorDzeng, RJen_US
dc.contributor.authorChang, SYen_US
dc.date.accessioned2014-12-08T15:37:09Z-
dc.date.available2014-12-08T15:37:09Z-
dc.date.issued2005-01-01en_US
dc.identifier.issn0926-5805en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.autcon.2004.06.003en_US
dc.identifier.urihttp://hdl.handle.net/11536/25531-
dc.description.abstractSeeking information from websites has become an essential part of a contractor's procurement undertaking. as more and more procurement websites become available on the Internet, Websites host extremely lame amounts of information: a keyword search, therefore, is often more efficient than browsing via an index. However. in order to find the desired information. it may be necessary to enter keywords using a trial-and-error process. This research recognizes that professional procurement experience can help users search website information more effectively, by using fewer keywords. and so proposes a learning model and suggestion model that can capture such experience. thus guiding inexperienced users in their search. Experiments, evaluating the performance of the system, were also conducted. (C) 2004 Elsevier B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectprocurementen_US
dc.subjectinformation searchen_US
dc.subjectmachine learningen_US
dc.subjecte-commerceen_US
dc.titleLearning search keywords for construction procurementen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.autcon.2004.06.003en_US
dc.identifier.journalAUTOMATION IN CONSTRUCTIONen_US
dc.citation.volume14en_US
dc.citation.issue1en_US
dc.citation.spage45en_US
dc.citation.epage58en_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.identifier.wosnumberWOS:000226496400004-
dc.citation.woscount2-
Appears in Collections:Articles


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