DocumentCode
161050
Title
Enhanced data processing using positive negative association mining on AJAX data
Author
Doshi, Montu ; Roy, Bidisha
Author_Institution
St. Francis Inst. of Technol., Mumbai Univ., Mumbai, India
fYear
2014
fDate
4-5 April 2014
Firstpage
386
Lastpage
390
Abstract
Knowledge discovery is the process of analyzing data from different perspectives and summarizing it into useful information. Association rule mining is a data mining process used widely in traditional databases to find the positive association rules. Association rules are created by analyzing data for frequent patterns and by using the criteria support and confidence to identify the most important relationships. However, there are some other challenging rule mining topics like negative association rule mining. In this research, a rule mining approach has been proposed that provides efficient and secure solution using positive and negative association rule computation on Asynchronous JavaScript and XML (AJAX) data. By using AJAX, we get the search result in the form of semantic data. Whenever data search from database is intended, the next possible word of the search will be made available.
Keywords
Java; XML; data analysis; data mining; AJAX data; asynchronous JavaScript and XML data; data analysis process; data mining process; data search; enhanced data processing; frequent pattern mining; knowledge discovery; positive negative association rule mining; Algorithm design and analysis; Association rules; Data processing; Databases; Information technology; XML; AJAX; Apriori Algorithm; Association rule mining; Database; Frequent Pattern-Growth (FP-Growth) Algorithm; Horizontal Tree Approach;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits, Systems, Communication and Information Technology Applications (CSCITA), 2014 International Conference on
Conference_Location
Mumbai
Type
conf
DOI
10.1109/CSCITA.2014.6839292
Filename
6839292
Link To Document