COMPARATIVE STUDY OF APRIORI AND FP-GROWTH ALGORITHM IN HORIZONTALLY PARTITIONED DATA USING CLIENT SERVER APPROACH

COMPARATIVE STUDY OF APRIORI AND FP-GROWTH ALGORITHM IN HORIZONTALLY PARTITIONED DATA USING CLIENT SERVER APPROACH
Author(s):
Ankita Sahu, Priyanka Pitale
Keywords:
Data Mining, Distributed database, Association rule mining, frequent pattern.
Abstract
Data mining is one of the important fields of computer science, which deals with mining of important information from the data. Association rule mining is one of the association rule mining technique is getting very popular now a days and is getting much more attention from the researchers. Mining data from distributed database is also one of the important aspect of data mining very data of one site is not known to the other site. This research paper focus on Comparative Study of Apriori and FP-Growth algorithm in Horizontally Partitioned Data using Client Server Approach and software is implemented in NETBEANS IDE 8.2. Concepts of Client Server technology is being used for implementation of distributed database.
Article Details
Unique Paper ID: 145161 Publication Volume & Issue: Volume 4, Issue 7 Page(s): 555 - 559
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