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Mining complaints to improve a product: A study about problem phrase extraction from user reviews

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dc.contributor.author Tutubalina E.
dc.date.accessioned 2018-09-19T22:55:23Z
dc.date.available 2018-09-19T22:55:23Z
dc.date.issued 2016
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/145763
dc.description.abstract © 2016 Copyright held by the owner/author(s).The rapidly growing availability of user reviews has become an important resource for companies to detect customer dissatisfaction from textual opinions. There have been few recent studies conducted on business-related opinion tasks to extract more refined opinions about a product's quality problems or technical failures. The focus of this study is the extraction of problem phrases, mentioned in user reviews about products. We explore main opinion mining tasks to determine whether given text from reviews contains a mention of a problem. We formulate research questions and propose knowledge-based methods and probabilistic models to classify users' phrases and extract latent problem indicators, aspects and related sentiments from online reviews.
dc.subject Opinion mining
dc.subject Problem phrase extraction
dc.subject User reviews
dc.title Mining complaints to improve a product: A study about problem phrase extraction from user reviews
dc.type Conference Paper
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 699
dc.source.id SCOPUS-2016-SID84964343948


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  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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