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Context-Aware Strategies For Recommender System On A Professional SNS Platform

Zhao, X, Liu, H, Tian, W, Zeng, Z and Ye, L (2013) Context-Aware Strategies For Recommender System On A Professional SNS Platform In: the 2nd International Conference on Computer Science and Electronics Engineering, 2013-03-22 - 2013-03-22, Hangzhou, China.

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Abstract

The importance of recommender system on Social Network Services (SNS) platform has been recognized by researchers and practitioners in many disciplines, including ecommerce, information retrieval, social computing, data mining, marketing, etc. While a substantial amount of approaches focus on recommending the most relevant items to users on mainstream SNS platforms, there is still a lack of closer investigation into the context-aware strategies on professional SNS platform whose contextual information varies significantly from generic SNS platforms. Drawing upon existing algorithmic paradigms –content-based methods and collaborative filtering, this paper proposes context-aware strategies that cope with the need to recommend both users and items on a professional SNS platform. A case study has been demonstrated based on such approach and directions for future research have been discussed.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Tourism
Divisions : Faculty of Arts and Social Sciences > School of Hospitality and Tourism Management
Authors :
AuthorsEmailORCID
Zhao, XUNSPECIFIEDUNSPECIFIED
Liu, HUNSPECIFIEDUNSPECIFIED
Tian, WUNSPECIFIEDUNSPECIFIED
Zeng, ZUNSPECIFIEDUNSPECIFIED
Ye, LUNSPECIFIEDUNSPECIFIED
Date : 3 March 2013
Identification Number : https://doi.org/10.2991/iccsee.2013.189
Copyright Disclaimer : Published by Atlantis Press, Paris, France. © the authors
Depositing User : Symplectic Elements
Date Deposited : 07 Mar 2017 16:23
Last Modified : 07 Mar 2017 16:23
URI: http://epubs.surrey.ac.uk/id/eprint/813407

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