期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2015
卷号：12
期号：3
出版社：IJCSI Press
摘要：The data mining is vast field with application found in many areas such that science, industrial problems and business. The data mining system architecture has the several main components database, data warehouse, or other information repositories, a server that extract the related data from repositories based on user request. The classification tasks in massive data set have been done by Varity of proposed algorithm. Majority of algorithm has proved effective but not all of them are easily extensible and flexible. This research introduce various approaches such to find useful result. This can be overcome by grouping of similar so clustering is a distinct problem. Then there is full-text search in large text collections which is robust against errors on both query and documents side. The paper discusses content-based recommendation systems that recommend an item to a user based upon a description of the item and a profile of the users interests. The paper also uses improved Boyer Moore Horspool algorithm for evaluation of Enhanced pattern matching performance and lastly Association rules mining that finds interesting relations or associations relations between the item sets among massive amount of data.
关键词：Apriori;Association rule; FORBD Dynamic; Boyer Moore Horspool algorithm; Extensional definition of dynamic association rules; Partial Decision Tree; data mining; evolutionary algorithms; rule;based classifiers; decision trees
