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چکیده

Mining association rules in large database is one of most popular data mining techniques for business decision makers. Discovering frequent item set is the core process in association rule mining. Numerous algorithms are available in the literature to find frequent patterns . Apriori and FP-tree are the most common methods for finding frequent items. Apriori finds significant frequent items using candidate generation with more number of data base scans. FP-tree uses two database scans to find significant frequent items without using candidate generation. This proposed T-VPIS (Tree - valuable package of item sets Method) discovers significant frequent items by generating full candidates once to form valuable package tree with one database scan. Experimental results of T-VPIS shows that this algorithm outperforms than Apriori and FP-tree to finding valuable set of items .

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مقالات و منابع مورد مطالعه

1) Boosted Apriori: an Effective Data Mining Association Rules for Heart Disease Prediction System

R. Thanigaivel and K. Ramesh Kumar Middle-East Journal of Scientific Research 24 (1): 192-200, 2016 ISSN 1990-9233 © IDOSI Publications, 2016 DOI: 10.5829/idosi.mejsr.2016.24.01.22944

2) Four Chechpoint Modified Aprior Algorithm for Data Minig in Accident Analysis

Shivangi Dheer & Miss. Priyanka Punjabi Gyan Vihar University

Imperial Journal of Interdisciolinary Research (IJIR) Vol-2,Issuse-7 ,2016 ISSN : 2452-1362 , http://www.onlinejournal.in


3) An Efficient Frequent Pattern Mining Algorithm to Find the Existence of

K-Selective Interesting Patterns in Large Dataset Using SIFPMM

Saravanan Suba Department of Computer Science, Kamarajar Government Arts College, Surandai-627859, Tamil Nadu, India. Dr. Christopher. T Department of Computer Science, Government Arts College, Coimbatore-641018, Tamil Nadu, India.

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 7 (2016) pp 5038-5045 ©Research India Publications. http://www.ripublication.com


4)Data Mining: Concepts and Techniques, 3rd Edition

Author(s):Han & Kamber&Pei Release Date:25 Jul 2011 Imprint:Morgan Kaufmann Print Book ISBN :9780123814791