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Aspect based Sentiment Analysis for travel and tourism in Myanmar Language using LSTM

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dc.contributor.author Maw, Soe Yu
dc.contributor.author Khine, May Aye
dc.date.accessioned 2019-07-22T08:38:46Z
dc.date.available 2019-07-22T08:38:46Z
dc.date.issued 2019-02-27
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1190
dc.description.abstract Big social data analytics is an important tool which can be used to reveal the important insight of the information from the social user. It is an approach which combines various statistical methods, sentiment analysis, multimedia management and social media analytics for forecasting and predicting people and analyzing trends. In Myanmar, most of people use social media, especially Facebook, to express their opinion about specific topic in Myanmar language. Customer's comment and reviews are valuable, and are important source of data for multiple purposes. There are various method were introduced for performing sentiment analysis, still there are not efficient in extracting the sentiment features from a given context of text. In this paper, aspect based sentiment analysis of hotels’ and restaurants’ reviews using Long Short-Term Memory (LSTM) is proposed. en_US
dc.language.iso en en_US
dc.publisher Seventeenth International Conference on Computer Applications(ICCA 2019) en_US
dc.subject Sentiment Analysis en_US
dc.subject Long Short-Term Memory en_US
dc.subject Big social data analysis en_US
dc.title Aspect based Sentiment Analysis for travel and tourism in Myanmar Language using LSTM en_US
dc.type Article en_US

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