Resources Aggregation Approach Based On Collaborative Tagging

Web2.0is a Web which gives to the social dimension, called the social machine, its share of contribution in the evolution of the Web through its uses. The process of association of a tag (metadata) to a document which can be in type of: text, image, video; by several users is called collaborative tagging.Collaborative tagging provides services for users to store, manage and search web resources with the help of freely chosen keywords, called "tags". Because of the high-volume usage of these systems and the annotations that users provide by their tags, these systems are regarded as good targets for disciplines like knowledge discovery. Roughly, two lines of research have been pursued so far on collaborative tagging: to study the structure of tags and to study their functionality in web search.Tagging systems contain large numbers of redundant, ambiguous, and idiosyncratic tags which can render resource discovery difficult. Data mining techniques such as clustering can be used to ameliorate this problem by reducing noise in the data and identifying trends. In particular, discovered patterns can be used to tailor the system’s output to a user based on the user’s tagging behavior. In this research The websites which implement this process don’t form a homogeneous unit; various techno-organizational characteristics make it possible to differentiate them, our objective was to study the different approaches to collaborative tagging in order to propose a solution that can "Aggregate tagged content" by different users, through focusing on the relations of "tags","users" and "web resources", three main components of any collaborative-tagging system, Our research is based on three stages, the first stage is clustering and structuring the folksonomy, the second stage the enrichment of the user’s query and the last step is to aggregate (group) the tagged resources.