Usage-driven Evolution of Personal Ontologies, Peter Haase, York Sure Andreas Hotho, Lars Schmidt-Thieme Download

Large information repositories as digital libraries, online shops, etc. rely on a taxonomy of the objects under consideration to structure the vast contents and facilitate browsing and searching (e.g., ACM topic classification for computer science literature, Amazon product taxonomy, etc.). As in heterogeneous communities users typically will use different parts of such an ontology with varying intensity, customization and personalization of the ontologies is desirable. In this paper we adapt a collaborative filtering recommender system to assist users in the management and evolution of their personal ontology by providing detailed suggestions of ontology changes. Such a system has been implemented in the context of Bibster, a peer-to-peer based personal bibliography management tool. Finally, we report on an in-situ experiment with the Bibster community that shows the performance improvements over non-personalized recommendations.

Personalized Learning in Web-Based Intelligent Educational Systems: Technologies and Techniques, Ioannis Hatzilygeroudis, Jim Prentzas, John Garofalakis Download

In this paper, we present technologies and techniques used in web-based intelligent educational systems (WBIESs). As WBIESs we consider either web-based intelligent tutoring systems (ITSs) or adaptive hypermedia education systems (AHESs) incorporating intelligent techniques. We present technologies and techniques for all the three basic components of a WBIES: the domain knowledge, the student modelling unit and the pedagogical module. The technologies and techniques come from two fields, artificial intelligence (AI) and adaptive hypermedia (AH). At the end, we outline possible key trends and technologies for future WBIESs.

Evaluating a system for enhanced access to statistical data on the Web: the StatSearch evaluation experiments, Ing-Mari Boynton, Bert Fridlund, Alf Fyhrlund, Peter Lundquist, Bo Sundgren, Martin Rajman, Martin Vesely, Helge Thelander, Martin Wänerskär Download

In this contribution we present an implementation of a user-based evaluation of an interactive information access system for enhanced access to statistical data on the web that has been realized in collaboration between EPFL, Statistics Sweden (SCB), and CERN, in the framework of the NEMIS network of excellence. The goal of the evaluation was to identify potential of the StatSearch prototype and its added value to information access as objectively perceived by users. The specification of the prototype evaluation is presented, based on supervised on-site usability testing.

A Methodology for Evaluating the Personalization Conceptual Schema of a Web Application, Evangelos Sakkopoulos, Spiros Sirmakessis, Athanasios Tsakalidis, Giannis Tzimas Download

While the market needs evolve rapidly, personalization has assumed an enormous industrial impact, which has caused a "Cambrian explosion" of technologies, claiming support to the personalization process. Deploying a methodology for the design and development of a Web application enhances effectiveness, but does not guarantee optimization in the design process, mainly due to the fact that a small number of extreme designers/programmers exist. The goal of this paper is to argue the need to approach personalization aspects from the very beginning in the Web application's development cycle. Since personalization is a key issue in the application's success, it is important that it should be dealt through a design view, rather than only an implementation view. In this paper, we will provide a methodology in order to evaluate the conceptual schema of an application, by means of the personalization features incorporated in the application model. The aim is to capture cases in which different ways are used to obtain the same personalization effect. We introduce the notion of model clones as partial conceptual schemas that are repeated within a broader application model. We define metrics to automate the detection and categorization of candidate model clones in order to facilitate potential model refactoring. Finally, we discuss possible model refactoring procedures with respect to personalization enhancements and detection of personalization defects.

Á Web Clipping Service's Information Extraction Mechanism, Christos Bouras, Giorgos Kounenis, Ioannis Misedakis Vasilis Poulopoulos Download

Information overload is one of the most important problems of today's WWW. Users are often lost in a wealth of information when searching about a topic. Although they have specific information needs, using a search engine or regularly browsing in popular news sites for updates can lead them to search in tens or hundreds of possibly relevant pages or loose some updates that were interesting for them. One promising solution for this problem is "web-clipping" services. A service like this continuously searches the Web and whenever it finds a web page that might interest some users, it informs these users that they should visit this specific page. This paper describes the information extraction mechanism of a web-clipping service that is being designed as part of a larger project for information search and manipulation. This mechanism is used to extract information from web pages and find out which links should be followed.

Representing User Information Context with Ontologies, Ahu Sieg, Bamshad Mobasher, Robin Burke, Ganesh Prabu, Steve Lytinen Download

One of the key factors for accurate and effective information access is the user context. The critical elements that make up a user's information context include the semantic knowledge about the domain being investigated, the short-term information need as might be expressed in a query, and the user profiles that reveal long-term interests. In this paper, we propose a framework for contextualized information access that seamlessly combines these elements in order to effectively locate and provide the most appropriate result for users' information needs. In particular, we focus on integrating a user's query with semantic knowledge from an existing ontology to assist the user in information retrieval.

Real-time Navigation Recommendations: Integrating Selective Markov Models and Site Content, Diamanto Oikonopoulou, Maria Rigou, Spiros Sirmakessis Download

Understanding and modeling user online behavior, as well as predicting future requests, remains an open challenge for researchers, analysts and marketers. In this paper, we propose an efficient prediction schema based on the extraction of sequential navigation patterns from server log files, combined with web site content. Traversed paths are monitored, recorded and cleaned before being completed with cashed page views. After session and episode identification follows the construction of n-grams. Prediction is based upon a 5+ n-gram schema with all lower level n-grams participating, a procedure that resembles the construction of an All 5th-order Markov Model. The schema resolves the typical dilemma between precision and applicability by deploying the site's content and structuring for outputting a prediction for every possible state with small loss in precision. Moreover, the paper explores the potential extension of the schema to allow for fine-tuning between usage-based and semantic-based predictions by incorporating semantic web technologies.