SOCIAL TAGGING AS A CLASSIFICATION AND SEARCH STRATEGY.

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As connectivity increases and more bandwith becomes available on the Internet, information exchange also grows. The desire for ubiquitous computing and easy retrieval and sharing of information are therefore a stimulus for newer search strategies, which can well fit every single user with power and flexibility. The main objectives of this thesis are the study and evaluation of the recent user-centered approaches toward resource classification and retrieval, which are usually referred to as social tagging systems. In these systems the users are allowed to associate personal labels or tags to each search object, so creating a personal categorization. Furthermore, the individual tags are shared to the benefit of the community, resulting in a collaborative effort to documental categorization. Some aspects of these systems are however still unclear or unresolved and are therefore subject to investigation: the emergence of a common agreement on tags; the correlations between the number of users, tags and tagged objects; the identification of similar tags (e.g. synonyms), etc. Eventually, the weaknesses and the advantages of these systems will be evaluated with respect to the traditional search stategies.