Notice of RetractionAutomated ontology-based customer needs translation and representation

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

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.