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Identifying product features from customer reviews using hybrid dependency patterns
Joint Authors
Baharudin, Baharum
Khan, Khayr Allah
Khan, Aurangzeb
Source
The International Arab Journal of Information Technology
Issue
Vol. 11, Issue 3 (31 May. 2014)7 p.
Publisher
Publication Date
2014-05-31
Country of Publication
Jordan
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
In this paper we have addressed the problem of automatic identification of product features from customer reviews.
Costumers, retailors, and manufacturers are popularly using customer reviews on websites for product reputation and sales forecasting.
Opinion Mining application have been potentially employed to summarize the huge collection of customer reviews for decision making.
In this paper we have proposed hybrid dependency patterns to extract product features from unstructured reviews.
The proposed dependency patterns exploit lexical relations and opinion context to identify features.
Based on empirical analysis we found that the proposed hybrid patterns provide comparatively more accurate results.
The average precision and recall are significantly improved with hybrid patterns.
American Psychological Association (APA)
Khan, Khayr Allah& Baharudin, Baharum& Khan, Aurangzeb. 2014. Identifying product features from customer reviews using hybrid dependency patterns. The International Arab Journal of Information Technology،Vol. 11, no. 3.
https://search.emarefa.net/detail/BIM-334321
Modern Language Association (MLA)
Khan, Khayr Allah…[et al.]. Identifying product features from customer reviews using hybrid dependency patterns. The International Arab Journal of Information Technology Vol. 11, no. 3 (May. 2014).
https://search.emarefa.net/detail/BIM-334321
American Medical Association (AMA)
Khan, Khayr Allah& Baharudin, Baharum& Khan, Aurangzeb. Identifying product features from customer reviews using hybrid dependency patterns. The International Arab Journal of Information Technology. 2014. Vol. 11, no. 3.
https://search.emarefa.net/detail/BIM-334321
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-334321