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The Review of Socionetwork Strategies
Erschienen in: The Review of Socionetwork Strategies 2/2018

20.09.2018 | Research Note

Bookmarks Recommendation in Bibsonomy using Community Detection

verfasst von: Mahmoud Saoud, Zakaria Saoud

Erschienen in: The Review of Socionetwork Strategies | Ausgabe 2/2018

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Abstract

Several academic social networks have emerged to help researchers who need to search for documents relevant to their interests. The recommendation has been adopted in many websites to suggest relevant documents to users according to their profiles. However, many academic social networks and digital libraries still lack recommendations. In this paper, we propose a new document recommendation approach for the academic social bookmarking website: Bibsonomy. In our method, we use a community detection technique to identify related users. Then, for each target user, the recommended documents are selected from their learning communities. Experimental results show that the proposed method performs better than state-of-the-art recommendation methods.
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Fußnoten
8
Knowledge and Data Engineering Group, University of Kassel: Benchmark Folksonomy Data from BibSonomy, version of January 01st, 2016. http://​bibsonomy.​org/​.
 
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Metadaten
Titel
Bookmarks Recommendation in Bibsonomy using Community Detection
verfasst von
Mahmoud Saoud
Zakaria Saoud
Publikationsdatum
20.09.2018
Verlag
Springer Japan
Erschienen in
The Review of Socionetwork Strategies / Ausgabe 2/2018
Print ISSN: 2523-3173
Elektronische ISSN: 1867-3236
DOI
https://doi.org/10.1007/s12626-018-0024-7

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