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Aspect based Sentiment Analysis for travel and tourism in Myanmar Language using LSTM
http://hdl.handle.net/20.500.12678/0000003441
http://hdl.handle.net/20.500.12678/0000003441c842df01-c70d-4236-9436-71773488a795
ecd488b5-3924-4192-8b54-59b93a555a14
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Title | ||||||
Title | Aspect based Sentiment Analysis for travel and tourism in Myanmar Language using LSTM | |||||
Language | en | |||||
Publication date | 2019-02-27 | |||||
Authors | ||||||
Maw, Soe Yu | ||||||
Khine, May Aye | ||||||
Description | ||||||
Big social data analytics is an importanttool which can be used to reveal the importantinsight of the information from the social user. It isan approach which combines various statisticalmethods, sentiment analysis, multimedia managementand social media analytics for forecasting andpredicting people and analyzing trends. In Myanmar,most of people use social media, especiallyFacebook, to express their opinion about specifictopic in Myanmar language. Customer's commentand reviews are valuable, and are important sourceof data for multiple purposes. There are variousmethod were introduced for performing sentimentanalysis, still there are not efficient in extracting thesentiment features from a given context of text. In thispaper, aspect based sentiment analysis of hotels’ andrestaurants’ reviews using Long Short-Term Memory(LSTM) is proposed. | ||||||
Keywords | ||||||
Sentiment Analysis, Long Short-Term Memory, Big social data analysis | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/1190 | |||||
Journal articles | ||||||
Seventeenth International Conference on Computer Applications(ICCA 2019) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |