Looking for Like-minded Individuals in Social Networks Using Tagging and Fuzzy Sets

The web is perceived as a new social platform. Very often, the users look at the web as a place where they can find individual or group of people with the same or similar interests, or even find new friends. Such situation is reflected in one of the aspects of the web 2.0 called tagging. Tagging is a process of labeling (annotating) digital items resources by users. The labels tags assigned to those resources reflect users ways of seeing, categorizing, and perceiving particular items. In general, a single user can label a number of items with a number of different tags. The results of this activity labelled items and used tags can be perceived as information characterizing the user. This paper describes an approach for constructing user signature representing her interests and opinions based on used items and tags. The signature is determined as a fuzzy relation built on two fuzzy sets proposed here: a fuzzy set representing resource attractiveness, and a fuzzy set representing tag popularity. Furthermore, users signatures are used to determine similarity between users, and potentially give users a method to find new web friends with similar interests and options. The paper also describes a process of building different signatures representing a group of users. Signatures of users that are members of the group are aggregated using OWA operator and different linguistic quantifiers to describe the group in a number of ways. A real-world case study illustrating the process of finding similar users and/or groups of users is included.