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Context determines content: an approach to resource recommendation in folksonomies

Rodenhausen, Thomas ; Anjorin, Mojisola ; Dominguez Garcia, Renato ; Rensing, Christoph (2012)
Context determines content: an approach to resource recommendation in folksonomies.
In: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web
doi: 10.1145/2365934.2365938
Book Section, Bibliographie

Abstract

By means of tagging in social bookmarking applications, so called folksonomies emerge collaboratively. Folksonomies have shown to contain information that is beneficial for resource recommendation. However, as folksonomies are not designed to support recommendation tasks, there are drawbacks of the various recommendation techniques. Graph-based recommendation in folksonomies for example suffers from the problem of concept drift. Vector space based recommendation approaches in folksonomies suffer from sparseness of available data. In this paper, we propose the flexible framework VSScore which incorporates context-specific information into the recommendation process to tackle these issues. Additionally, as an alternative to the evaluation methodology LeavePostOut we propose an adaptation LeaveRTOut for resource recommendation in folksonomies. In a subset of resource recommendation tasks evaluated, the proposed recommendation framework VSScore performs significantly more effective than the baseline algorithm FolkRank.

Item Type: Book Section
Erschienen: 2012
Creators: Rodenhausen, Thomas ; Anjorin, Mojisola ; Dominguez Garcia, Renato ; Rensing, Christoph
Type of entry: Bibliographie
Title: Context determines content: an approach to resource recommendation in folksonomies
Language: English
Date: September 2012
Publisher: ACM
Book Title: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web
Series: RSWeb '12
Event Location: Dublin, Ireland
DOI: 10.1145/2365934.2365938
URL / URN: ftp://ftp.kom.tu-darmstadt.de/papers/RADR12.pdf
Abstract:

By means of tagging in social bookmarking applications, so called folksonomies emerge collaboratively. Folksonomies have shown to contain information that is beneficial for resource recommendation. However, as folksonomies are not designed to support recommendation tasks, there are drawbacks of the various recommendation techniques. Graph-based recommendation in folksonomies for example suffers from the problem of concept drift. Vector space based recommendation approaches in folksonomies suffer from sparseness of available data. In this paper, we propose the flexible framework VSScore which incorporates context-specific information into the recommendation process to tackle these issues. Additionally, as an alternative to the evaluation methodology LeavePostOut we propose an adaptation LeaveRTOut for resource recommendation in folksonomies. In a subset of resource recommendation tasks evaluated, the proposed recommendation framework VSScore performs significantly more effective than the baseline algorithm FolkRank.

Uncontrolled Keywords: collaborative tagging, context, folksonomy, ranking, recommender systems, social media, vector space
Identification Number: TUD-CS-2012-0387
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Multimedia Communications
Profile Areas
Profile Areas > Cybersecurity (CYSEC)
Date Deposited: 28 Aug 2017 14:21
Last Modified: 17 Apr 2019 12:12
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