A review selection method using product feature taxonomy
Tian, Nan, Xu, Yue, & Li, Yuefeng (2014) A review selection method using product feature taxonomy. In Web Information Systems Engineering - WISE 2014: 15th International Conference, Proceedings, Part I [Lecture Notes in Computer Science, Volume 8786], Springer, Thessaloniki, Greece, pp. 408-417.
As of today, online reviews have become more and more important in decision making process. In recent years, the problem of identifying useful reviews for users has attracted significant attentions. For instance, in order to select reviews that focus on a particular feature, researchers proposed a method which extracts all associated words of this feature as the relevant information to evaluate and find appropriate reviews. However, the extraction of associated words is not that accurate due to the noise in free review text, and this affects the overall performance negatively. In this paper, we propose a method to select reviews according to a given feature by using a review model generated based upon a domain ontology called product feature taxonomy. The proposed review model provides relevant information about the hierarchical relationships of the features in the review which captures the review characteristics accurately. Our experiment results based on real world review dataset show that our approach is able to improve the review selection performance according to the given criteria effectively.
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|Item Type:||Conference Paper|
|Keywords:||Review Selection, Review Quality, Review Model, Ontology, Product Feature Taxonomy|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000)|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > School of Information Technology
|Copyright Owner:||Copyright 2014 [please consult the author]|
|Deposited On:||08 Sep 2014 04:46|
|Last Modified:||15 Oct 2014 14:17|
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