NDLI: PaWI: Parallel Weighted Itemset Mining by Means of MapReduce

Content Provider	IEEE Xplore Digital Library
Author	Baralis, E. Cagliero, L. Garza, P. Grimaudo, L.
Copyright Year	2015
Description	Author affiliation: Dipt. di Autom. e Inf., Politec. di Torino, Turin, Italy (Baralis, E.; Cagliero, L.; Garza, P.; Grimaudo, L.)
Abstract	Frequent item set mining is an exploratory data mining technique that has fruitfully been exploited to extract recurrent co-occurrences between data items. Since in many application contexts items are enriched with weights denoting their relative importance in the analyzed data, pushing item weights into the item set mining process, i.e., Mining weighted item sets rather than traditional item sets, is an appealing research direction. Although many efficient in-memory weighted item set mining algorithms are available in literature, there is a lack of parallel and distributed solutions which are able to scale towards Big Weighted Data. This paper presents a scalable frequent weighted item set mining algorithm based on the MapReduce paradigm. To demonstrate its action ability and scalability, the proposed algorithm was tested on a real Big dataset collecting approximately 34 millions of reviews of Amazon items. Weights indicate the ratings given by users to the purchased items. The mined item sets represent combinations of items that were frequently bought together with an overall rating above average.
Starting Page	25
Ending Page	32
File Size	191314
Page Count	8
File Format	PDF
e-ISBN	9781467372787
DOI	10.1109/BigDataCongress.2015.14
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Weight measurement Algorithm design and analysis Itemsets Scalability And association rules Clustering algorithms Classification Big data Data mining H.2.8.b Clustering
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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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