Abstract
Recommender systems have become important tools to support users in identifying relevant content in an overloaded information space. To ease the development of recommender systems, a number of recommender frameworks have been proposed that serve a wide range of application domains. Our TagRec framework is one of the few examples of an open-source framework tailored towards developing and evaluating tag-based recommender systems. In this paper, we present the current, updated state of TagRec, and we summarize and re.ect on four use cases that have been implemented with TagRec: (i) tag recommendations, (ii) resource recommendations, (iii) recommendation evaluation, and (iv) hashtag recommendations. To date, TagRec served the development and/or evaluation process of tag-based recommender systems in two large scale European research projects, which have been described in 17 research papers. .us, we believe that this work is of interest for both researchers and practitioners of tag-based recommender systems.
Original language | English |
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Title of host publication | UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization |
Publisher | Association of Computing Machinery |
Pages | 23-28 |
Number of pages | 6 |
ISBN (Electronic) | 9781450350679 |
DOIs | |
Publication status | Published - 9 Jul 2017 |
Event | 25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017 - Bratislava, Slovakia Duration: 9 Jul 2017 → 12 Jul 2017 |
Conference
Conference | 25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017 |
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Country/Territory | Slovakia |
City | Bratislava |
Period | 9/07/17 → 12/07/17 |
Keywords
- Hashtag recommendation
- Recommendation evaluation
- Recommender framework
- Recommender systems
- Tag recommendation
ASJC Scopus subject areas
- Software