Service Mining: A Service Intelligent System to Explore Valuable Services in Big Data Analysis and Mining Technology
- National Taichung University of Science and Technology
Abstract
In recent years, rapid development of the Internet leads to overloaded service information. Therefore, finding services that correspond to their needs in the shortest time from substantial service information becomes a key challenge for consumers. Multiple platforms have emerged to assist customers in finding suitable services through systems. However, most of these platforms are product-oriented, mainly using product characteristics as filtering principles. Accordingly, the service intelligent system of this study identifies items strongly associated with valuable services based on the service value of customer preferences, and recommends them to the customer based on the service-dominant logic. This system applies the RFM approach and the apriori algorithm of association rules to design a service intelligent system. To verify the feasibility of the established service intelligent system, three experiments were conducted: screening core customers, analyzing preferred services of core customers, and generating a recommended valuable service set by adopting tourism data, which includes 62,575 valid customers with 72,244 valid travel records, from the Taiwan Tourism Bureau of the Ministry of Transportation and Communication. Hence, to assess the performance of this service intelligent system, a fourth experiment was designed to compare with the Apriori algorithm and analyze precision, recall, and fallout. The experiment results significantly reveal that valuable services are then recommended to the customers, enabling them and the enterprises to jointly create service value via the service intelligent system.
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