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- Mining Association Rules Using Formal Concept Analysis
Authors
Source
International Journal of Innovative Research and Development, Vol 3, No 12 (2014), Pagination:Abstract
In this paper, we present a methodology based on formal concept analysis (FCA) for the Knowledge Discovery process. We show that FCA can be useful for understanding conceptual model. We focus on Association Rule Mining and formal concept analysis for Booksales transaction database. Formal concept analysis deals with formal mathematical tools and techniques to develop and analyze the relationship between concepts and to develop concept structures.
Given a set of transactions, the problem of mining association rules is to discover all the rules that have user specified minimum support Minimum Confidence by implementing lattice concepts and implications rules.
Keywords
Association Rulemining, minimum support, minimum confidence, formal concept analysis, lattice.- Mining of Temporal Optimal High Utility Item Sets from Data Streams
Authors
Source
International Journal of Innovative Research and Development, Vol 2, No 12 (2013), Pagination:Abstract
Temporal High Utility Item (THUI) mining has become an emerging research topic in the data mining field, and finding frequent item sets is an important task in data mining with wide applications. Two basic factors to be considered in utility mining. First, the utility (e.g., profitability, time) of each item may be different in real applications; second, the frequent itemsets might not produce the highest utility. In this paper, we propose a novel algorithm named TOUIG (Temporal Optimal Utility Item Set Generation) which can find optimal high utility item sets from database. A novel approach namely, TOUI-tree (Temporal Optimal Utility Item set tree), is also proposed for efficiently capturing the utility of each item set with one-time scanning. The main contributions of this paper are as follows: 1) OUIG is the first one-pass utility-based algorithm for mining temporal optimal utility item sets and the experimental results show that our approach produces optimized solution than other existing utility mining algorithms.