NDLI: Efficient Personalized Recommendation of Mobile Web Content Using an EM-Based Clustering Method

Content Provider	IEEE Xplore Digital Library
Author	Ming He Chin, A. Enhong Chen Jilei Tian
Copyright Year	2014
Description	Author affiliation: Xpress Internet Services, Microsoft, Beijing, China (Chin, A.; Jilei Tian) \|\| Sch. of Comput. Sci., Univ. of Sci. & Technol. of China, Hefei, China (Ming He; Enhong Chen)
Abstract	Many applications recommend personalized content to users based on their interests. However, personalized recommendation is time and memory consuming especially for commercial systems that have huge numbers of users, requests and big data that require complex computation. Since users do not totally have unique interests, we can cluster similar users then recommend the same items to users belonging in the same cluster. Even though clustering-based recommendations are efficient, the recommendation items to users may not be accurate. We present an Expectation-Maximization (EM) based personalized recommendation method for selecting the appropriate items efficiently and accurately. We use a browser log dataset to compare our method with personalized, k-means, and EM-based recommendations according to average rank, novelty, diversity, and time performance. Results show that based on average rank, novelty and diversity, our proposed method performs close to that of personalized, however it is less efficient than k-means. Since k-means has the worst average rank, novelty and diversity, our method is the best overall.
Starting Page	152
Ending Page	159
File Size	363688
Page Count	8
File Format	PDF
ISBN	9781479962396
DOI	10.1109/CIT.2014.88
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uniform resource locators Accuracy mobile content recommendation k-means clustering Filtering Clustering algorithms EM clustering Personalized recommendation Vectors Browsers History
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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