Abstract--A new approach to the online classification of streaming data is introduced in this paper. It is based on a selfdeveloping (evolving) fuzzy-rule-based (FRB) classifier sy...
Abstract. In this paper we present a rule-based personalization framework for encapsulating and combining personalization algorithms known from adaptive hypermedia and recommender ...
In this paper, we present new approaches to handling drift and shift in on-line data streams with the help of evolving fuzzy systems (EFS), which are characterized by the fact tha...
Most recommendation methods (e.g., collaborative filtering) consist of (1) a computationally intense offline phase that computes a recommender model based on users’ opinions o...
Justin J. Levandoski, Mohamed Sarwat, Mohamed F. M...
Researchers from the same lab often spend a considerable amount of time searching for published articles relevant to their current project. Despite having similar interests, they c...