Clustering Unanimous Web Users Based on Rating and User-signature

The new social networking era allows and makes users to use web as a place to find people with common interest. People do often search for someone who is of similar interest. People’s interest can be found with the few options in web known as tagging and rating. A single user can rate a single item based on his likeness on that item. This paper describes a way on how to identify unanimous people with the tags and rating. A user-signature is constructed by establishing a set representing resource tag and its rating with an algorithm. User signature is generated as a text string specifying the category id and its rating average. Further, signatures of various users are compared and the scale of unanimity is found using an algorithm. A group of users are formed who are likeminded. The group is formed by applying a parameter based clustering with parametric group signature.