An efficient online system of concept based association rules mining

This paper presents a new text mining system for extracting association rules based on concepts from online textual documents. The system is called developed extracting association rules from textual documents. The mathematical formula of weighting schema is used for labeling the documents automatically and its named fuzzy weighting schema. A new algorithm is proposed for generating association rules based on concepts and it used a data structure of hash table for the mining process. The experiments are applied on a collection of scientific documents that selected from MEDLINE for breast cancer treatments and side effects. The performance of proposed system is compared with the previous Apriori-concept system for the execution time and the evaluation of the extracted association rules. The results show that the number of extracted association rules in the proposed system is always less than that in Apriori-concept system. Moreover, the execution time of proposed system is much better than Apriori-concept system in all cases.

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