Adaptive Web sites: automatically synthesizing Web pages
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
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There are two problems in online retail: 1) The different interest of all customers in the different commodities conflicts with the commodity classification structure of the web site; 2) Customers will simultaneously buy some commodities that are classified in different classes and levels in the web site. The two problems will make the majority of customers access overabundant web pages. To solve these problems, we mine the web data to build a hidden markov model, use association rule discovery to get the large item sets, use Viterbi algorithm to find some paths, mark the large item sets in the nodes of the paths. The large item sets will compete in the nodes for the limited space. Through this approach the web site will adjust itself to reduce the total access times of all users. This method also can be used in analyzing paths, advertisements, and reconstructing the web site.