Duc Hong Pham and Anh Cuong Le (2016) A Least Square based Model for Rating Aspects and Identifying Important Aspects on Review Text Data. In: SW4PHD: the 2016 Scientific Workshop for PhD Students, 26 March 2016, Hanoi.
In recent years, opinion mining and sentiment analysis has been one of the attracting topics of knowledge mining and natural language processing. The problem of rating aspects from textual reviews is an important task in this field. In this paper we propose a new method for rating product aspects as well as for identifying important aspects in general. Our proposed model is based on the least square method and the QR decomposition technique. In our experiment, we use a dataset of 594810 reviews of 3775 hotels collected from the very famous website in tourism tripadvisor.com with five common aspects including cleanliness, location, service, room and value. Experimental result shows that our proposed method outperforms some well known studies for the same problem.
|Item Type:||Conference or Workshop Item (Poster)|
|Subjects:||Information Technology (IT)|
|Divisions:||Faculty of Information Technology (FIT)|
|Deposited By:||Dr Ngoc Thang Bui|
|Deposited On:||23 May 2016 03:13|
|Last Modified:||23 May 2016 03:14|
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