Frequent Closed Item Set Mining Based on Zero-suppressed BDDs
نویسندگان
چکیده
منابع مشابه
Generating Frequent Closed Item Sets Based on Zero-suppressed BDDs
(Abstract) Frequent item set mining is one of the fundamental techniques for knowledge discovery and data mining. In the last decade, a number of efficient algorithms for frequent item set mining have been presented, but most of them focused on just enumerating the item set patterns which satisfy the given conditions, and it was a different matter how to store and index the result of patterns f...
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(Abstract) In this paper, we propose a method for discovering hidden information from large-scale item set data based on the symmetry of items. Symmetry is a fundamental concept in the theory of Boolean functions, and there have been developed fast symmetry checking methods based on BDDs (Binary Decision Diagrams). Here we discuss the property of symmetric items in data mining problems, and des...
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Frequent item set mining is one of the best known and most popular data mining methods. Originally developed for market basket analysis, it is used nowadays for almost any task that requires discovering regularities between (nominal) variables. This paper provides an overview of the foundations of frequent item set mining, starting from a definition of the basic notions and the core task. It co...
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Real life transaction data often miss some occurrences of items that are actually present. As a consequence some potentially interesting frequent item sets cannot be discovered, since with exact matching the number of supporting transactions may be smaller than the user-specified minimum. In order to allow approximate matching during the mining process, we propose an approach based on transacti...
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In present paper, we propose a new method of n-gram analysis using ZBDDs (Zero-suppressed BDDs). ZBDDs are known as a compact representation of combinatorial item sets. Here, we newly apply the ZBDD-based techniques for efficiently handling sets of sequences. Using the algebraic operations defined over ZBDDs, such as union, intersection, difference, etc., we can execute various processings and/...
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ژورنال
عنوان ژورنال: Transactions of the Japanese Society for Artificial Intelligence
سال: 2007
ISSN: 1346-0714,1346-8030
DOI: 10.1527/tjsai.22.165