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Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user's navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content, and user profile data. Due to the explosive growth of the(More)
Web personalization is the process of customizing a web site to the needs of each specific user or set of users. Personalization of a web site may be performed by the provision of recommendations to the users, high-lighting/adding links, creation of index pages, etc. The web personalization systems are mainly based on the exploitation of the navigational(More)
Social network analysis has emerged as a key technique in modern sociology, but has recently gained a lot of interest in Web mining research, because of the advent and the increasing popularity of social media, such as blogs, social networks, micro-blogging, customer review sites etc. Such media often serve as platforms for information dissemination and(More)
Web personalization is the process of customizing a Web site to the needs of each specific user or set of users, taking advantage of the knowledge acquired through the analysis of the user's navigational behavior. Integrating usage data with content, structure or user profile data enhances the results of the personalization process. In this paper, we(More)
Relational database systems are becoming increasingly popular in the scientific community to support the interactive exploration of large volumes of data. In this scenario, users employ a query interface (typically, a web-based client) to issue a series of SQL queries that aim to analyze the data and mine it for interesting information. First-time users,(More)
Markov models have been widely used for modelling users' navigational behaviour in the Web graph, using the transitional probabilities between web pages, as recorded in the web logs. The recorded users' navigation is used to extract popular web paths and predict current users' next steps. Such purely usage-based probabilistic models, however, present(More)
The amounts of information residing on web sites make users' navigation a hard task. To address this problem, web sites provide recommendations to the end users, based on similar users' navigational patterns mined from past visits. In this paper we introduce a recommendation method, which integrates usage data recorded in web logs, and the conceptual(More)