Multilevel Relationship Algorithm for Association Rule Mining used for Cooperative Learning
نویسندگان
چکیده
منابع مشابه
Multilevel Relationship Algorithm for Association Rule Mining used for Cooperative Learning
Mining the Data is also known as Discovery of Knowledge in Databases. It is to get correlations, trends, patterns, anomalies from the databases which can help to build exact future decisions. However data mining is not the natural. No one can assure that the decision will lead to good quality results. It only helps experts to understand the data and show the way to good decisions. Association M...
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over the years, a variety of algorithms for finding frequent item sets in very large transaction databases have been developed. The problems of finding frequent item sets are basic in multi level association rule mining, fast algorithms for solving problems are needed. This paper presents an efficient version of apriori algorithm for mining multi-level association rules in large databases to fi...
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These Association rule mining is to find association rules that satisfy the predefined minimum support and confidence from a given database. The Apriori and FP-tree algorithms are the most common and existing frequent itemsets mining algorithm, but these algorithms lack incremental learning ability. Incremental learning ability is desirable to solve the temporal dynamic property of knowledge an...
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The Transactions in web data often consist of quantitative data, suggesting that fuzzy set theory can be used to represent such data. The time spent by users on each web page is one type of web data, was regarded as a trapezoidal membership function (TMF) and can be used to evaluate user browsing behavior. The quality of mining fuzzy association rules depends on membership functions and since t...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2014
ISSN: 0975-8887
DOI: 10.5120/14973-3169