Data Science, considered as a science by itself, is in general terms, the extraction of
knowledge from data. Symbolic data analysis (SDA) gives a new way of thinking in Data …

Mobile recommender systems target on recommending the right product or information to
the right mobile users at anytime and anywhere. It is well known that the contextual …

Web service recommendation has become a hot yet fundamental research topic in service
computing. The most popular technique is the Collaborative Filtering (CF) based on a user …

While many studies on typical recommender systems focus on making recommendations to
individual users, social activities usually involve groups of users. Issues related to group …

Frequent Web navigation patterns generated by using Web usage mining techniques
provide valuable information for several applications such as Web site restructuring and …

Users of a Web site usually perform their interest-oriented actions by clicking or visiting Web
pages, which are traced in access log files. Clustering Web user access patterns may …

Most recommendation systems are implemented using numerical or categorical data, that is,
traditional data. This type of data can be a limiting factor when used to model complex …

With the development of wireless telecommunication technologies, a number of studies
have been done on the issues of location-based services due to wide applications. Among …

Symbolic polygonal data analysis is a new type of framework to extract valuable knowledge
from a new structure of data using regular polygon built from data in class, big data, and …

In this paper, we propose and investigate the effectiveness of fully decentralized,
collaborative filtering techniques. These are particularly interesting for use in pervasive …