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dc.contributor.authorDe Abrew, KMA
dc.contributor.authorKumara, PPNV
dc.contributor.authorVidanagama, DU
dc.date.accessioned2018-05-22T08:25:52Z
dc.date.available2018-05-22T08:25:52Z
dc.date.issued2016
dc.identifier.urihttp://ir.kdu.ac.lk/handle/345/1259
dc.descriptionArticle full texten_US
dc.description.abstractCustomer opinions hold a very important place in businesses, especially for companies and hotels. In last years, opinions have become more important due to global Internet usage as opinions pool. The opinion mining is one of the most popular topics in Text mining and Natural Language Processing. Unfortunately, looking through customer reviews and pulling out information to improve their service is a difficult work due to the large number of existing reviews. It is identified that there is no such an automated system to mine and extract information from consumer opinions in Sri Lanka for hotel industry. The proposed system focuses on the problem of opinion mining, particularly applied to hotel reviews and targets to develop a system that is capable of extracting and classifying different opinions automatically, based on the sentiments polarity. The objectives of this research are: Study the existing problem of opinion mining of Hotel Reviews in Sri Lanka, study the technologies and tools to solve the problem, develop a prototype to solve the identified problem of opinion mining and to test and evaluate the proposed solution. The proposed solution presents a system to mine client opinions, classify them as positive, negative or neutral. This system mine the reviews and summarize them for the ease of decision making.The system uses Sentiment Word Net based method for opinion mining from hotel reviews and sentence relevance score based method for opinion summarization of hotel reviews. The proposed system will save the time of consumers by providing the summarized opinions.Also this website allow users to search for hotels based on category and the location according to the ratings.In addition this will help the higher authorities by making decisions and improve the services based on opinions of customers.en_US
dc.language.isoenen_US
dc.subjectOpinion mining,en_US
dc.subjectCustomer feedbacken_US
dc.subjectSentiment classificationen_US
dc.titleAn Integrated Framework for Opinion Mining and Summarization of Hotel Reviewsen_US
dc.typeArticle Full Texten_US
dc.identifier.journalKDU IRCen_US
dc.identifier.issueComputingen_US
dc.identifier.pgnos13-17en_US


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