NDLI: Incremental iterative time spent based ranking model for online activitybased friend-group recommendation systems

Content Provider	IEEE Xplore Digital Library
Author	Jose, S.V. Madhavu, M.
Copyright Year	2015
Description	Author affiliation: Dept. of CSE, SBCE, Alappuzha, India (Jose, S.V.; Madhavu, M.)
Abstract	Online social networks enhance user experience by connecting users with similar interests. Online friend recommendation is a rapid developing field in data mining. Current social networking services prescribe friends to users in light of their social graphs and mutual friends, which may not be the most proper to reflect a user's taste on friend selection in real lifetime. In this paper propose a system that recommends companions based on the daily activities of users. Here a semantic based friend recommendation is done based on the user's life styles such as posting, chatting, searching, commenting etc. By using text mining technique, we display a user's daily life as life archives, from which his/her ways of life are separated by using the Latent Dirichlet Allocation algorithm. At that point we discover a similarity metric to quantify the similarity of life styles between users as an incremental way, and ascertain user effect as far as ways of life with a similarity matching diagram. Then calculate user impact ranking iterative matrix vector multiplication strategy in user incrementally, so that it would be versatile to vast scale frameworks. Ranking is mainly based on time spent on activities, profile information and feedback factor. At last, we incorporate a feedback component to further improve the proposal precision.
Starting Page	1
Ending Page	6
File Size	973562
Page Count	6
File Format	PDF
e-ISBN	9781479979844
DOI	10.1109/ICCCNT.2015.7395175
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Social network services Geology Games Activity recognition Social networks Pattern recognition Similarity metric Indexes Data mining
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
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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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