%0 Generic %1 karthikeyan2013modifed %A Karthikeyan, J %A Udaykumar, Dr. %B 2013 Mobile Communication - I %D 2013 %E Kaushik, Dr. B K %I ACEEE (A Computer division of IDES) %K Apriori Data frequent item-sets mining %T Modifed Bit-Apriori Algorithm for Frequent Item- Sets in Data Mining %U http://searchdl.org/public/book_series/LSCS/2/66.pdf %X Mining frequent item-sets is one of the most important concepts in data mining. It is a fundamental and initial task of data mining. Apriori3 is the most popular and frequently used algorithm for finding frequent item-sets. There are other algorithms viz, Eclat4, FP-growth5 which are used to find out frequent item-sets. In order to improve the time efficiency of Apriori algorithms, Jiemin Zheng introduced Bit-Apriori1 algorithm with the following corrections with respect to Apriori3 algorithm. 1) Support count is implemented by performing bitwise “And” operation on binary strings 2) Special equal-support pruning In this paper, to improve the time efficiency of Bit-Apriori1 algorithm, a novel algorithm that deletes infrequent items during trie2 and subsequent tire’s are proposed and demonstrated with an example.

@conference{karthikeyan2013modifed, abstract = {Mining frequent item-sets is one of the most important concepts in data mining. It is a fundamental and initial task of data mining. Apriori[3] is the most popular and frequently used algorithm for finding frequent item-sets. There are other algorithms viz, Eclat[4], FP-growth[5] which are used to find out frequent item-sets. In order to improve the time efficiency of Apriori algorithms, Jiemin Zheng introduced Bit-Apriori[1] algorithm with the following corrections with respect to Apriori[3] algorithm. 1) Support count is implemented by performing bitwise “And” operation on binary strings 2) Special equal-support pruning In this paper, to improve the time efficiency of Bit-Apriori[1] algorithm, a novel algorithm that deletes infrequent items during trie2 and subsequent tire’s are proposed and demonstrated with an example.}, added-at = {2014-02-05T07:31:15.000+0100}, author = {Karthikeyan, J and Udaykumar, Dr.}, biburl = {https://www.bibsonomy.org/bibtex/25a93e2d663bb49eb3d0e6150a41c7a74/idescitation}, booktitle = {2013 Mobile Communication - I}, editor = {Kaushik, Dr. B K}, interhash = {b0f1721b684b829136566621d4a492bf}, intrahash = {5a93e2d663bb49eb3d0e6150a41c7a74}, keywords = {Apriori Data frequent item-sets mining}, organization = {Institute of Doctors Engineers and Scientists}, publisher = {ACEEE (A Computer division of IDES)}, timestamp = {2014-02-05T07:31:15.000+0100}, title = {Modifed Bit-Apriori Algorithm for Frequent Item- Sets in Data Mining}, url = {http://searchdl.org/public/book_series/LSCS/2/66.pdf}, year = 2013 }