Research on web association rules mining structure with genetic algorithm
Ya‐ling Tang, Feng Qin
Abstract
Ya‐ling Tang, Feng Qin
Abstract
Association rules are import basis of describing Web users' behavior characteristic. Traditional algorithms of Web association rules mining, based on statistics, usually pays attention to the analysis on existing data,they can't offer effective predictive means and optimizing measure and can not find out the latent and possible rules. This paper presents a kind of system of the Web association rules mining based on genetic algorithm, which proves by experiment that it can mend the traditional Web association mining method of lack of foreseeing in latency. And it puts forward a new ideal of Web association rules mining.
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Association rules are import basis of describing Web users' behavior characteristic. Traditional algorithms of Web association rules mining, based on statistics, usually pays attention to the analysis on existing data,they can't offer effective predictive means and optimizing measure and can not find out the latent and possible rules. This paper presents a kind of system of the Web association rules mining based on genetic algorithm, which proves by experiment that it can mend the traditional Web association mining method of lack of foreseeing in latency. And it puts forward a new ideal of Web association rules mining.
Key concepts: Association rule learning, Computer science, Web mining, Data mining, Association (psychology), Measure (data warehouse), Ideal (ethics), Web page