NDLI: CASW : Context Aware Sliding Window for Frequent Itemset Mining over Data Streams

Please wait, while we are loading the content...

CASW : Context Aware Sliding Window for Frequent Itemset Mining over Data Streams

Content Provider	Semantic Scholar
Author	Reddy, V. Sidda Rao, T. Venkateswara Govardhn, And A.
Copyright Year	2017
Abstract	In recent years, advances in both hardware and software technologies coupled with high-speed data generation leads data streams and data stream mining. Data generation has been much faster in data stream applications and score of data is generated in quick turnaround time. Hence it becomes obvious to perform mining, data on arrival that is usually termed as data stream mining. General frequent pattern mining methods are envisaging limitations and do not support in responding to a massive quantum of data being streamed. In order to address such limitations, data mining researchers have focused on methods for conducting more efficient and effective mining tasks by scanning a database only once. As a process of evolution, sliding window model that perform mining operations focusing on updating accumulated parts over data streams, are proposed. It is hard to consider all of the frequent patterns in data stream environment as generated patterns were remarkably increasing as data streams get extended continuously. Hence, methods for efficiently compressing patterns that are generated are essential to address the limitations. Considering the challenges and shortcoming in the earlier solutions, in this paper, focus is on incremental mining of frequent patterns from the window and a solution of CASW (Context Aware Sliding Window) is proposed. There are well defined boundaries for frequent and infrequent patterns for specific patterns. In this research article, we adapt usage of window size change for 184 V. Sidda Reddy, T.V.Rao and A.Govardhn representing conceptual drift in the information stream. An experimental study carried out on the model depicts significant developments and has affirmed that the algorithm has been designed with a more efficient system than that of existing solution.
File Format	PDF HTM / HTML
Alternate Webpage(s)	https://www.ripublication.com/ijcir17/ijcirv13n2_03.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in