Guiding Concept Generation Based on Ontology for Customer Preference Modeling

Customers often show different preferences relative to the same products, such as function, shape, color, costs, etc. They will surely affect product market activities further. In this paper, a model of preference elicitation from customers is proposed to reduce the gap between the systematic representation of preferences and customers’ actual preferences. Firstly, the attribute of customer preferences are classified by developing a kind of preference taxonomy which is analyzed to build customer preference ontological concepts and relationships. Secondly, the documents or catalogs of design requirements, perhaps containing some textual description and geometry data, are normalized by using ontology-based semantic expressions. Some semantic rules are developed to describe low-level features of customer preferences to build an ontological knowledge base towards customer preferences. Thirdly, customer needs are mapped to customer preference ontologies for driving high-level concept generations. A customer preference modeling framework is developed to construct a vector space model to measure the distance between sets of preferences. Finally, an empirical study is surveyed, and five different customer groups are queried towards the cell phone preferences. The query results are analyzed to represent validity of concept generation from customer preferences.