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Community-Based Recommendations: a Solution to the Cold Start Problem

Sahebi, Shaghayegh and Cohen, William (2011) Community-Based Recommendations: a Solution to the Cold Start Problem. In: Workshop on Recommender Systems and the Social Web (RSWEB), held in conjunction with ACM RecSys’11, 23 October 2011 - 23 October 2011, Chicago.

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Abstract

The “Cold-Start” problem is a well-known issue in recommendation systems: there is relatively little information about each user, which results in an inability to draw inferences to recommend items to users. In this paper, we try to give a solution to this problem based on homophily in social networks: we can use social networks’ information in order to fill the gap existing in cold-start problem and find similarities between users. In this study, we use communities, extracted from different dimensions of social networks, to capture the similarities of these different dimensions and accordingly, help recommendation systems to work based on the found latent similarities. By different dimensions, we mean friendship network, item similarity network, commenting network and etc.

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Details

Item Type: Conference or Workshop Item (Paper)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Sahebi, Shaghayeghshs106@pitt.eduSHS106
Cohen, William
Date: October 2011
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Event Title: Workshop on Recommender Systems and the Social Web (RSWEB), held in conjunction with ACM RecSys’11
Event Dates: 23 October 2011 - 23 October 2011
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Intelligent Systems
Refereed: No
Related URLs:
Date Deposited: 05 Aug 2012 13:34
Last Modified: 25 Aug 2017 05:06
URI: http://d-scholarship.pitt.edu/id/eprint/13328

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