Title: A method of product feature usability analysis based on web semantic mining

Authors: Huijun Long; Liya Wang; Pan Liu

Addresses: Sino-US Global Logistics Institute, Shanghai Jiao Tong University, No. 1954 Huashan Road, 200030 Shanghai, China; School of Economics & Management, Changzhou University, No. 1 Gehu Road, 213164 Changzhou, China ' Sino-US Global Logistics Institute, Shanghai Jiao Tong University, No. 1954 Huashan Road, 200030 Shanghai, China; Department of Industrial Engineering & Logistics Management, Shanghai Jiao Tong University, No. 800 Dongchuan Road, 200240, Shanghai, China ' Department of Industrial Engineering & Logistics Management, Shanghai Jiao Tong University, No. 800 Dongchuan Road, 200240 Shanghai, China

Abstract: Product usability is an evaluation indicator of customer satisfaction with product features and functions. Questionnaire survey is traditional methods widely used in product feature usability analysis. In fact, it is labour intensive and time consuming. Nowadays, with the rapid expansion of web, more and more customers tend to express their opinions on products through it. As a result, the number of reviews on certain product grows rapidly. This paper proposes a novel method based on web semantic mining of Chinese customer reviews to analyse product feature usability. First, useful information corresponding to product feature usability, such as customers' reviews of products, is extracted from webs based on the semantic mining technology with an information system, called Web Miner. Then the product feature usability is measured and evaluated by evaluation model. Finally, usability analysis of Nokia 5230 is used as a case to validate the proposed method.

Keywords: web mining; mobile phones; cell phones; product features; customer review; usability analysis; product usability; customer satisfaction; China; customer reviews.

DOI: 10.1504/IJSOI.2012.051393

International Journal of Services Operations and Informatics, 2012 Vol.7 No.2/3, pp.136 - 149

Received: 02 Dec 2011
Accepted: 03 Aug 2012
Published online: 27 Dec 2014 *

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