Decision Tree Formation and Fuzzy Similarity Matching for Duplicates Detection

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Authors : S.Sindhu, Ms.R.Suganya
Publication Date: 17-09-2013


Author(s):  S.Sindhu, Ms.R.Suganya

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Vol.2 - Issue 9 (September - 2013)

e-ISSN:   2278-0181


The duplicate detection is the most important process needed in world to find the duplicates. Several algorithms fail to detect the accurate duplicate in the hierarchal data. Our method to detect duplicates is the combination of Decision Tree and Fuzzy Similarity Matching. Duplicate detection, which is an important subtask of data cleaning, is the task of identifying multiple representations of a same real-world object. In this paper is discussed to detect duplicate using the Decision tree is used to form the tree from the given input variables. Fuzzy Similarity Matching is used to match the variables and provide the probability value for the matching .Our goals are either on improving the quality of the detected duplicates (effectiveness) or on saving computation time (efficiency).


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