X. Jing, Penghao Wang, Julia M. Rayz
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引用次数: 6
Discovering Attribute-Specific Features From Online Reviews: What Is the Gap Between Automated Tools and Human Cognition?
Thisarticledescribeshowonlinereviewsplayanimportantroleindatadrivendecisionmaking. Manyeffortshavebeeninvestedindeterminingtheoverallsentimentcarriedbythereviews.However, oftentimes,theoverallratingsofthereviewsdonotrepresentopinionstowardspecificattributes ofaproduct.Anidealopinionminingtoolshouldaimatfindingboththeproductattributesand theircorrespondingopinions.Theauthorsproposeanapproachforextractingtheattributespecific featuresfromonlinereviewsusingaWord2Vecmodelcombinedwithclustering.Twoexperiments aredescribed in thispaper: thefirst focuseson testing theperformanceof theWord2Vecmodel onextractingproductaspectwords,thesecondaddresseshowwelltheextractedfeaturesobtained arerecognizablebyhumancognition.Anewmetriccalledthe“splitvalue”thatisbasedoncluster similarityanddiversityisintroducedtoexaminetheconsistencyofclusteringalgorithm.Theauthors’ experimentssuggestthatmeaningfulclusters,whichprovideinsightstotheproductattributesand sentiments,couldbeextractedfromthereviews. KeyWORDS Artificial Intelligence, Clustering, Cognition, Feature Extraction, Opinion Mining, Text Understand, Word2Vec
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