Data mining for VOD service consumption features research

Pao Yue-kong Library Electronic Theses Database

Data mining for VOD service consumption features research

 

Author: Xia, Jinguang
Title: Data mining for VOD service consumption features research
Degree: M.Sc.
Year: 2006
Subject: Hong Kong Polytechnic University -- Dissertations
Data mining
Video dial tone
Department: Dept. of Computing
Pages: 120 leaves : ill. ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b2069387
URI: http://theses.lib.polyu.edu.hk/handle/200/2568
Abstract: In the study of this dissertation, data mining methods have been used as a utility to discover the tacit inter-relationship from the Internet transaction records and classify the related customers' attributes to find the potential new entrants in value-added business. In the recent years, a large amount of investment on IT infrastructure has greatly improved the service scale in telecommunication operation domain. So far, .the imminent need for turning the huge amount of data into useful information-knowledge, has been an interesting problem. This study is wrapped up with a case study in value-added service to illustrate how to translate data into information and how to reveal the tacit interrelationship from millions of records of business transactions. Data preparing, data mining implementation and decision support have all been involved in this study. Not only a road map, but also implementation details have been discussed in this study to prove that data mining is a combination of technology and business skills. Clustering and classifying methods have been used in this research to illustrate the effect of data mining to discover the tacit knowledge and reveal the potential new entrants in cross-sell analysis. The results have been extracted by the data mining research and described as the marketing strategy to help the enterprise to improve their competition advantage. These results have been compared with the previous research to show the efficiency of the data mining approach. Finally, by appraising the discovered knowledge, a conclusion has been made that the practice of data mining delivery the value to marketing strategies in these three aspects: first, analyzing the transaction records to show the tacit knowledge to the business decision-maker; second, reducing the marketing cost to obtain the new customers; showing data mining as an effective and reasonable method in customer behavior research.

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