Folksonomy and Tag-Based Recommender Systems in E-Learning Environments
Collaborative tagging is technique, highly employed in different domains, which is used for automatic analysis of users’ preferences and recommendations. To improve recommendation quality, metadata such as content information of items has typically been u
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Folksonomy and Tag-Based Recommender Systems in E-Learning Environments
Abstract Collaborative tagging is technique, highly employed in different domains, which is used for automatic analysis of users’ preferences and recommendations. To improve recommendation quality, metadata such as content information of items has typically been used as additional knowledge. With the increasing reputation of the collaborative tagging systems, tags could be interesting and provide useful information to enhance algorithms for recommender systems. Besides helping user to organize his/her personal collections, a tag also can be regarded as a user’s personal opinion expression, while tagging can be considered as implicit rating or voting on the tagged information resources or items. The overview, presented in this chapter includes descriptions of content-based recommender systems, collaborative filtering systems, hybrid approach, memory-based and model-based algorithms, features of collaborative tagging that are generally attributed to their success and popularity, as well as a model for tagging activities and tag-based recommender systems.
Collaborative tagging is a technique, highly employed in different domains, which is used for automatic analysis of users’ preferences and recommendations. To improve recommendation quality, metadata such as content information of items has typically been used as additional knowledge. With the increasing reputation of the collaborative tagging systems, tags could be interesting and useful information to enhance algorithms for recommender systems. Collaborative tagging systems allow users to upload their resources, and to label them with arbitrary words, so-called tags (Golder and Huberman 2006). The systems can be distinguished according to what kind of resources they supported. Flickr,1 for instance, allows the sharing of photos, del.icio.us2 the sharing of bookmarks, CiteULike3 and Connotea4 the sharing of bibliographic references, and 43Things5 even the sharing of goals in 1
http://www.flickr.com. http://www.del.icio.us. 3 http://www.citeulike.org. 4 http://www.connotea.org. 5 http://www.43things.com. 2
© Springer International Publishing Switzerland 2017 A. Klašnja-Milićević et al., E-Learning Systems, Intelligent Systems Reference Library 112, DOI 10.1007/978-3-319-41163-7_7
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private life. Essentially, all these systems are very similar. Once a user is logged in, (s)he can add a resource to the system, and assign arbitrary tags. The collection of all his assignments is his personomy, the collection of all personomies constitutes the folksonomy. The user can explore his personomy, as well as the personomies of the other users, in all dimensions: for a given user one can see all resources (s)he had uploaded, together with the tags (s)he had assigned to them (Jäschke et al. 2007). Besides helping user to organize his/her personal collections, a tag also can be regarded as a user’s personal opinion expression, while tagging can be cons
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