Pham, Duc Hong and Le, Anh Cuong and Le, Thi Kim Chung (2015) A Least Square based Model for Rating Aspects and Identifying Important Aspects on Review Text Data. In: NICS: 2nd National Foundation for Science and Technology Development Conference on Information and Computer Science, 16-18 September 2015, Ho Chi Minh city, Vietnam.
Full text not available from this repository.Abstract
Opinion mining and sentiment analysis has been one of the attracting topics of knowledge mining and natural language processing in recent years. 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. The experiments are carried out on the data collected from hotel services with the aspects including the cleanliness, location, service, room, and value. We have obtained more accurate results than some well-known previous studies.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | data mining;least squares approximations;natural language processing;text analysis;cleanliness;hotel services;knowledge mining;least square based model;location;natural language processing;opinion mining;rating product aspects;review text data;room;sentiment analysis;service;value;Algorithm design and analysis;Computer science;Dictionaries;Hidden Markov models;Mathematical model;Prediction algorithms;Training |
| Subjects: | Information Technology (IT) |
| Depositing User: | Prof. Xuan-Tu Tran |
| Date Deposited: | 28 Dec 2015 02:59 |
| Last Modified: | 28 Dec 2015 02:59 |
| URI: | http://eprints.uet.vnu.edu.vn/eprints/id/eprint/1461 |
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