Automated Ontology-based Customer Needs Translation and Representation
Intense competition and high failure product rate calls for a deeper understanding of customer needs. However, the process of translation and interpretation of voice of customers (VoC) into customer needs statements involves much imprecise information with linguistic vague descriptions. In order to get accurate customer need statements and further to further to enhance customer satisfaction for product success, we have to take a review of how to well interpret, translate and represent customer needs in the front-end product design process. We endow the use of ontology is an efficient approach for accurate custom needs translation and representation. Although ontology is promising for our target, it is known that manually building ontology is a tedious work, which requires much human effort. To solve this problem, we present a framework that automatically translates and represents customers needs in the form of ontology in this paper. We first employ natural language processing tools to pre-process the customer statements. Then, a set of algorithms are used to extract concepts and relations from the processed statements, building the final ontology. We have conducted a case study of the framework. In particular, the customer statements about digital camera products are collected from customer reviews. Then, we build ontology from the collected statement. The experimental results demonstrate the efficacy of our framework.
Customer needs representation natural language processing ontology construction ontology learning
Chen Xingyu Chen Chun-hsien Leong Kah Fai
Department of Systems and Engineering Management, Nanyang Technological University, Singapore
国际会议
北京
英文
907-910
2011-08-08（万方平台首次上网日期，不代表论文的发表时间）