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Toward an adaptive string similarity measure for matching product offers

dc.contributor.authorThor, Andreas
dc.contributor.editorFähnrich, Klaus-Peter
dc.contributor.editorFranczyk, Bogdan
dc.date.accessioned2019-01-11T10:12:10Z
dc.date.available2019-01-11T10:12:10Z
dc.date.issued2010
dc.description.abstractProduct matching aims at identifying different product offers referring to the same real-world product. Product offers are provided by different merchants and describe products using textual attributes such as offer title and description. String similarity measures therefore play an important role for matching corresponding product offers. In this paper, we propose an adaptive string similarity measure that automatically adjusts the relevance of terms for the product matching. This adaptation is done step-by-step during the match process and does not require training data. We demonstrate that this approach improves the match quality in comparison to the generic TFIDF string similarity measure.en
dc.identifier.isbn978-3-88579-269-7
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/19128
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2010. Service Science – Neue Perspektiven für die Informatik. Band 1
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-175
dc.titleToward an adaptive string similarity measure for matching product offersen
dc.typeText/Conference Paper
gi.citation.endPage710
gi.citation.publisherPlaceBonn
gi.citation.startPage702
gi.conference.date27.09.-1.10.2010
gi.conference.locationLeipzig
gi.conference.sessiontitleRegular Research Papers

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