Dimitrios Pierrakos

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This paper is a survey of recent work in the ¢eld of web usage mining for the bene¢t of research on the personalization of Web-based information services. The essence of personalization is the adaptability of information systems to the needs of their users. This issue is becoming increasingly important on the Web, as non-expert users are overwhelmed by the(More)
This paper presents a knowledge discovery framework for the construction of Community Web Directories, a concept that we introduced in our recent work, applying personalization to Web directories. In this context, the Web directory is viewed as a thematic hierarchy and personalization is realized by constructing user community models on the basis of usage(More)
SUMMARY This paper presents the Web Usage Mining system KOINOTITES, which uses data mining techniques for the construction of user communities on the Web. User communities model groups of visitors in a Web site, who have similar interests and navigational behaviour. We present the architecture of the system and the results that we obtained in a real Web(More)
This paper improves a recently-presented approach to Web Personalization, named Community Web Directories, which applies per-sonalization techniques to Web Directories. The Web directory is viewed as a concept hierarchy and personalization is realized by constructing user community models on the basis of usage data collected by the proxy servers of an(More)
This paper introduces a new approach to Web Personaliza-tion, named Web Community Directories that aims to tackle the problem of information overload on the WWW. This is realized by applying personalization techniques to the well-known concept of Web Directories. The Web directory is viewed as a concept hierarchy which is generated by a content-based(More)
We propose a knowledge framework for garment recommendations, which is based on two pillars. The first pillar incorporates knowledge about aspects of fashion, such as materials, garments, colours, body types, facial features, social occasion etc., as well as their interrelations, with the purpose of providing personalised recommendations. The said knowledge(More)
This paper presents the concept of Web Community Directories, as a means of personalizing services on the Web, together with a novel methodology for the construction of these directories by document clustering and usage mining methods. The community models are extracted with the use of the Community Directory Miner, a simple cluster mining algorithm which(More)
We present a method for modeling user navigation on a web site using grammatical inference of stochastic regular grammars. With this method we achieve better models than the previously used first order Markov chains, in terms of predictive accuracy and utility of recommendations. In order to obtain comparable results, we apply the same grammatical inference(More)
Community Web Directories constitute a form of personal-ization performed on Web directories, such as the Open Directory Project (ODP). They correspond to " segments " of the directory hierarchy, representing the interests and preferences of user communities and thus provide a personalized view of the Web. In this paper, we present OurDMOZ, a system that(More)
This paper introduces the concept of Web Community Directories, as a means of personalizing services on the Web, and presents a novel methodology for the construction of these directories by usage mining methods. The community models are extracted with the use of the Community Directory Miner, a simple cluster mining algorithm which has been extended to(More)