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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD)
An International Open Access Journal |   ISSN: 2456-4184 |  IMPACT FACTOR: 5.57

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Paper Title: Multi Objective Fuzzy Association Rule Mining with ABC Algorithm
Authors Name: Patel Alok Balavantbhai , Mr. Premkumar Shivakumar
Author Reg. ID:
IJNRD_170164
Published Paper Id: IJNRD1711012
Published In: Volume 2 Issue 11, November-2017
Abstract: Data Mining is the process of obtaining high level knowledge by automatically discovering information from data in the form of rules and patterns. Data mining seeks to discover knowledge that is accurate, comprehensible and interesting .Data mining is most commonly used in attempts to induce association rules from transaction data. Association rule mining is a well-established method of data mining that identifies significant correlations between items in transactional data. An association rule is an expression X Y, where X and Y are a set of items. It means in the set of transactions. If all the items in X exist in a transaction. Then Y is also in the transaction with a high probability. Fuzzy Association rule mining is an essential topic in Information retrieval mining field and produces all important Fuzzy association rules between attributes in the dataset because large data set records considered as transactions. Each transaction consists of set of attributes. Multi-objective is an area of multiple criteria decision making, that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. A MOO problem with constraints will have many solutions in the feasible region. Even though we may not be able to assign numerical relative importance to the multiple objectives, we can still classify some possible solutions as better than others. In ABC algorithm, the position of a food source represents a possible solution to the optimization problem and the nectar amount of a food source corresponds to the quality (fitness) of the associated solution. On inspecting the behavior of real bees on finding nectar and sharing the information of food sources to the bees in the hive. ABC seems particularly suitable for multi-objective optimization mainly because of solution quality and the high speed of convergence that the algorithm presents for single-objective optimization. Proposed work examines a new Multi-Objective Fuzzy Rule Mining with ABC algorithm.
Keywords: Data mining; Rule optimization, Artificial Bee Colony; Fuzzy Association rule mining, Multi-Objective
Cite Article: "Multi Objective Fuzzy Association Rule Mining with ABC Algorithm", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.2, Issue 11, page no.68-73, November-2017, Available :http://www.ijnrd.org/papers/IJNRD1711012.pdf
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