NDLI: A Study on the Improved Collaborative Filtering Algorithm for Recommender System

Content Provider	IEEE Xplore Digital Library
Author	Hee Choon Lee Seok Jun Lee Young Jun Chung
Copyright Year	2007
Description	Author affiliation: Sang-ji Univ., Wonju (Hee Choon Lee; Seok Jun Lee)
Abstract	The purpose of this study is to suggest an algorithm of a recommender system to increase the customer's desire of purchasing, by automatically recommending goods transacted on e-commerce to customers. The recommender system has various filtering techniques according to the methods of recommendation. In this study, researchers study collaborative filtering among recommender systems. The accuracy of customer's preference prediction is compared with the accuracy of customer's preference prediction of the existing collaborative filtering algorithm, and the suggested new algorithm. At first, the accuracy of a customer's preference prediction of neighborhood based algorithm as automated collaborative filtering algorithm firstly & correspondence mean algorithm, is compared. It is analyzed by using $MovieLens^{1}$ 100K dataset and I Million dataset in order to experiment with the prediction accuracy of the each algorithm. For similarity weight used in both algorithms it is discovered Pearson's correlation coefficient and vector similarity which are generally used were utilized, and as a result of analysis, we show that the accuracy of the customer's preference prediction of correspondence mean algorithm is superior. Pearson's correlation coefficient and vector similarity used in two algorithms are calculated by using the preference rating of two customers' co-rated movies, and it shows that similarity weight is overestimated, where the number of co-rated movies is small. Therefore, it is intended to increase the accuracy of customer's preference prediction through expanding the effect of the number of the existing co-rated movies.
Sponsorship	Int. Assoc. Comput. Inf. Sci.
Starting Page	297
Ending Page	304
File Size	321705
Page Count	8
File Format	PDF
ISBN	0769528678
DOI	10.1109/SERA.2007.33
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-20
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Collaboration Filtering algorithms Recommender systems Motion pictures Cities and towns Collaborative work Algorithm design and analysis Accuracy Software engineering Conference management
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

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