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 reflect 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. Thus, we believe that this work is of interest for both researchers and practitioners of tag-based recommender systems.
A considerable contribution to this area is http: wiki.librec.net doku.php , a Java-based library that, so far, comprises around 70 resource recommendation algorithms and evaluation modules @cite_6 . Another Java-based, open-source framework is http: ranksys.org , which focuses on the evaluation of ranking problems and supports the investigation of novelty as well as diversity for academic research @cite_29 , which is reflected in its design (e.g., data input interfaces work with a triple of user, item and features).
@cite_29 @cite_6
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The large array of recommendation algorithms proposed over the years brings a challenge in reproducing and comparing their performance. This paper introduces an open-source Java library that implements a suite of state-of-the-art algorithms as well as a series of evaluation metrics. We empirically find that LibRec performs faster than other such libraries, while achieving competitive evaluative performance. Summary: We describe multiple methods for accessing and querying the complex and integrated cellular data in the BioCyc family of databases: access through multiple file formats, access through Application Program Interfaces (APIs) for LISP, Perl and Java, and SQL access through the BioWarehouse relational database. Availability: The Pathway Tools software and 20 BioCyc DBs in Tiers 1 and 2 are freely available to academic users; fees apply to some types of commercial use. For download instructions see http: BioCyc.org download.shtml Supplementary information: For more details on programmatic access to BioCyc DBs, see http: bioinformatics.ai.sri.com ptools ptools-resources.html Contact: [email protected]