An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets
نویسندگان
چکیده
منابع مشابه
An Efficient Procedure for Mining Statistically Significant Frequent Itemsets
We suggest the original procedure for frequent itemsets generation, which is more efficient than the appropriate procedure of the well known Apriori algorithm. The correctness of the procedure is based on a special structure called Rymon tree. For its implementation, we suggest a modified sort-merge-join algorithm. Finally, we explain how the support measure, which is used in Apriori algorithm,...
متن کاملA Rigorous Statistical Approach for Identifying Significant Itemsets
As advances in technology allow for the collection, storage, and mining of vast amounts of data, the task of screening and assessing the significance of the discovered patterns is becoming a major challenge in data mining applications. In this work, we address significance in the context of frequent itemset mining. Specifically, we develop a novel methodology to identify a meaningful support th...
متن کاملFrequent Itemsets Mining: An Efficient Graphical Approach
Recent advances in computer technology in terms of speed, cost, tremendous amount of computing power and decrease data processing time has spurred increased interest in data mining applications to extract useful knowledge from data. Over the last couple of years, data mining technology has been successfully employed to various business domains and scientific areas. Various data mining technique...
متن کاملAn Efficient Approach for Text Clustering Based on Frequent Itemsets
In recent times, the vast amount of textual information available in electronic form is growing at staggering rate. This increasing number of textual data has led to the task of mining useful or interesting frequent itemsets (words/terms) from very large text databases and still it seems to be quite challenging. The use of such frequent itemsets for text clustering has received a great deal of ...
متن کاملAn Efficient Approach to Mining Frequent Itemsets on Data Streams
The increasing importance of data stream arising in a wide range of advanced applications has led to the extensive study of mining frequent patterns. Mining data streams poses many new challenges amongst which are the one-scan nature, the unbounded memory requirement and the high arrival rate of data streams. In this paper, we propose a new approach for mining itemsets on data stream. Our appro...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the ACM
سال: 2012
ISSN: 0004-5411,1557-735X
DOI: 10.1145/2220357.2220359