Abstract
The paper presented an intelligent commodity information search model, which integrates semantic retrieval andmulti-attribute decision method. First, semantic similarity is computed by constructing semantic vector-space, inorder to realize the semantic consistency between retrieved result and customer’s query. Besides, TOPSISmethod is also utilized to construct the comparison mechanism of commodity by calculating the utility value ofeach retrieved commodity. Finally, the experiment is conducted in terms of accuracy and customer acceptancerate, and the results verify the effectiveness of the model and it can improve the precision of the commodityinformation search.
Highlights
Nowadays, the advance of Internet and Web technologies has continuously boosted the prosperity of e-commerce
TOPSIS method is utilized to construct the comparison mechanism of commodity by calculating the utility value of each retrieved commodity, and choose the most suitable one for customers
In order to verify the effectiveness of search algorithm presented in the paper, a new assessment criterion of commodity information search can be defined in the paper, which is called Customer Acceptance Ration (CAR)
Summary
The advance of Internet and Web technologies has continuously boosted the prosperity of e-commerce. Wang presents a semantic-similarity based information search method (Wang 2006), which utilizes ontology to describe semantics of the customer queries and Web documents, and computes the semantic similarity between the concept and property of domain knowledge to realize the semantic information search. In order to solve the information overload of commodities and provide accurate information search and shopping service for customers, one kind of effective commodity evaluation and comparison mechanism should be constructed, which is based on the realization of semantic retrieval of general information. In order to realize it, the paper presents an intelligent commodity information search model of E-commerce search engine, which integrates semantic retrieval and multi-attribute decision method. The intelligent model considers the semantic search problems, and utilizes the commodity evaluation and comparison mechanism, in order to improve the precision ration of commodity information and provide intelligent shopping services for customers.
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