P-Tag

Abstract

The success of the Semantic Web depends on the availability of Web pages annotated with metadata. Free form metadata or tags, as used in social bookmarking and folksonomies, have become more and more popular and successful. Such tags are relevant keywords associated with or assigned to a piece of information (e.g., a Web page), describing the item and enabling keyword-based classification. In this paper we propose P-TAG, a method which automatically generates personalized tags for Web pages. Upon browsing a Web page, P-TAG produces keywords relevant both to its textual content, but also to the data residing on the surfer's Desktop, thus expressing a personalized viewpoint. Empirical evaluations with several algorithms pursuing this approach showed very promising results. We are therefore very confident that such a user oriented automatic tagging approach can provide large scale personalized metadata annotations as an important step towards realizing the Semantic Web.ACM 978-1-59593-654-7/07/0005. 1 Lowercase semantic web refers to an evolutionary approach for the Semantic Web by adding simple meaning gradually into the documents and thus lowering the barriers for re-using information. 2

Understanding why users tag: A survey of tagging motivation literature and results from an empirical study

“…In related work, the introduced distinction between categorizers and describers was used to demonstrate that emergent semantics in folksonomies are influenced by the users’ motivation for tagging [29]. However, the influence of tagging motivation on other areas of work, such as taxonomy learning from tagging systems [31], simulation of tagging processes [32] or tag recommendation [33], remains to be studied in future work.…”

Tagging diversity in personal learning environments

“…Among them, three prototypes are highly interesting and represent stereotypes called P-TAG (Chirita et al 2007), iTAG (Strohmaier et al 2009), and TagSense (Qin et al 2011). iTAG demonstrates the idea of intent tagging which explores the goals behind the applied tags.…”

“…We select SeViAnno ) and its mobile version AnViAnno, CCPLE ), YouTell and MobCamp , ROLE Language Widgets (Wolpers et al 2010), iTag (Strohmaier et al 2009), P-TAG (Chirita et al 2007), TagSense (Qin et al 2011), and some inversion-problem games (e.g., Taboo) introduced in Ahn and Dabbish (2008) as listed in Table 3. Tagging is not well applied for reflection phase.…”

A multi-layer framework for personalized social tag-based applications

“…Tag prediction is then carried out by suggesting to a given user the set of tags specified by other users with a similar profile, i.e., in the same cluster. An alternative approach is proposed in [6], where tags are predicted by extracting relevant terms from a resource, and then by computing their similarity with keywords representing the documents' corpus of the personal desktop of a given user. Other related works have been carried out in the context of Web services (see e.g., [17,18]).…”

“…In general, social tag-based applications gather metadata associated with resources, elaborate them and exploit the obtained results to trigger some actions (for example, resource recommendation, classification or filtering). Up to now, research on social tag-based applications has mainly focused on personalized recommendations of tags (e.g., [4][5][6]) or resources (e.g., [7][8][9][10]), which make use of techniques derived from the data mining area to predict which tags/resources might be relevant, and how much.…”