Literature Survey of modern frequent item set mining methods |
Author(s): |
| Prof. Anand Rajavat , Shri Vaishnav Institute of Technology & Science Indore, India; Mohammad Mudassar Khan, Shri Vaishnav Institute of Technology & Science Indore, India |
Keywords: |
| Data Mining, Frequent Itemset, Broglet's FP-Growth, SaM Algorithm |
Abstract |
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In this paper, we present an overview of existing frequent item set mining algorithms. All these algorithms are described more or less on their own. Frequent item set mining is a very popular and computationally expensive task. We also explain the fundamentals of frequent item set mining. We describe today's approaches for frequent item set mining. From the broad variety of efficient algorithms that have been developed we will compare the most important ones. We will systematize the algorithms and analyse their performance based on both their run time performance and theoretical considerations. Their strengths and weaknesses are also investigated. It turns out that the behaviour of the algorithms is much more similar as to be expected. |
Other Details |
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Paper ID: IJSRDV1I5057 Published in: Volume : 1, Issue : 5 Publication Date: 01/08/2013 Page(s): 1272-1273 |
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