Mining association rules between sets of items in large databases
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SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
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Mining association rules with adjustable accuracy
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Selected papers from the sixth international conference on World Wide Web
Modern Information Retrieval
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
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WISE '00 Proceedings of the First International Conference on Web Information Systems Engineering (WISE'00)-Volume 1 - Volume 1
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An efficient searching system is needed to offer the exact result of diverse web information to the user. Due to this reason, it is important to extract and analyze the user requirements in the distributed information environment. The searching method proposed in this paper uses the keyword as well as its context information for effective searching. Moreover, the proposed searching method is extracted keywords by using the new keyword extraction method also proposed in this paper, and it is executed web searching based on keyword mining profile generated by the extracted keywords. Unlike the conventional searching method, which searched for information by representative words, the proposed searching method is more efficient and exact. This is because data are searched by the example-based query including the content information as well as the representative words. Moreover, this searching method makes a domain keyword list for a quick search. The domain keyword is the representative word of a special domain. The performance of the proposed algorithm is analyzed in a series of experiments to identify its various characteristics.