Personalized content retrieval in context using ontological knowledge

Personalized content retrieval aims at improving the retrieval process by taking into account the particular interests of individual users. However, not all user preferences are relevant in all situations. It is well known that human preferences are complex, multiple, heterogeneous, changing, even contradictory, and should be understood in context with the user goals and tasks at hand. In this paper, we propose a method to build a dynamic representation of the semantic context of ongoing retrieval tasks, which is used to activate different subsets of user interests at runtime, in a way that out-of-context preferences are discarded. Our approach is based on an ontology-driven representation of the domain of discourse, providing enriched descriptions of the semantics involved in retrieval actions and preferences, and enabling the definition of effective means to relate preferences and context

Guided generation of pedagogical concept maps from the Wikipedia

We propose a new method for guided generation of concept maps from open accessonline knowledge resources such as Wikies. Based on this method we have implemented aprototype extracting semantic relations from sentences surrounding hyperlinks in the Wikipedia’sarticles and letting a learner to create customized learning objects in real-time based oncollaborative recommendations considering her earlier knowledge. Open source modules enablepedagogically motivated exploration in Wiki spaces, corresponding to an intelligent tutoringsystem. The method extracted compact noun–verb–noun phrases, suggested for labeling arcsbetween nodes that were labeled with article titles. On average, 80 percent of these phrases wereuseful while their length was only 20 percent of the length of the original sentences. Experimentsindicate that even simple analysis algorithms can well support user-initiated information retrievaland building intuitive learning objects that follow the learner’s needs.Peer reviewe

Organization and Usage of Learning Objects within Personal Computers

Research report of the ProLearn Network of Excellence (IST 507310), Deliverable 7.6To promote the integration of Desktop related Knowledge Management and Technology Enhanced Learning this deliverable aims at increasing the awareness of Desktop research within the Professional Learning community and at familiarizing the e-Learning researchers with the state-of-the-art in the relevant areas of Personal Information Management (PIM), as well as with the currently on-going activities and some of the regular PIM publication venues

requirements and use cases

In this report, we introduce our initial vision of the Corporate Semantic Web as the next step in the broad field of Semantic Web research. We identify requirements of the corporate environment and gaps between current approaches to tackle problems facing ontology engineering, semantic collaboration, and semantic search. Each of these pillars will yield innovative methods and tools during the project runtime until 2013. Corporate ontology engineering will improve the facilitation of agile ontology engineering to lessen the costs of ontology development and, especially, maintenance. Corporate semantic collaboration focuses the human-centered aspects of knowledge management in corporate contexts. Corporate semantic search is settled on the highest application level of the three research areas and at that point it is a representative for applications working on and with the appropriately represented and delivered background knowledge. We propose an initial layout for an integrative architecture of a Corporate Semantic Web provided by these three core pillars

Adaptive hypertext and hypermedia : workshop : proceedings, 3rd, Sonthofen, Germany, July 14, 2001 and Aarhus, Denmark, August 15, 2001

This paper presents two empirical usability studies based on techniques from Human-Computer Interaction (HeI) and software engineering, which were used to elicit requirements for the design of a hypertext generation system. Here we will discuss the findings of these studies, which were used to motivate the choice of adaptivity techniques. The results showed dependencies between different ways to adapt the explanation content and the document length and formatting. Therefore, the system's architecture had to be modified to cope with this requirement. In addition, the system had to be made adaptable, in addition to being adaptive, in order to satisfy the elicited users' preferences

Adaptive hypertext and hypermedia : workshop : proceedings, 3rd, Sonthofen, Germany, July 14, 2001 and Aarhus, Denmark, August 15, 2001

This paper presents two empirical usability studies based on techniques from Human-Computer Interaction (HeI) and software engineering, which were used to elicit requirements for the design of a hypertext generation system. Here we will discuss the findings of these studies, which were used to motivate the choice of adaptivity techniques. The results showed dependencies between different ways to adapt the explanation content and the document length and formatting. Therefore, the system's architecture had to be modified to cope with this requirement. In addition, the system had to be made adaptable, in addition to being adaptive, in order to satisfy the elicited users' preferences

WISM 2005 : web information systems modeling

Modern Web Information Systems (WIS) need to satisfy a large number of requirements coming from different WIS stakeholders. Modeling WIS by focusing at one design aspect at-a-time helps the implementation of these requirements. During the last years several model-driven methodologies have been proposed to support the WIS design. Strategic modeling is usually the first step in WIS design. It is a very general characterization of WIS which answers questions like: what is the purpose of the WIS?, which are the WIS users?, what functionality is provided by the WIS?, what is the content of the WIS?, what is the layout and atmosphere of the presentations provided by the WIS?, etc. It is only after answering the above questions at a high abstract level that the designer can proceed with the detailed specifications of the WIS. Data integration is one of the most important characteristics of WIS. Some examples of domains in which data integration is present are: public services and bioinformatics. WIS need to support user interfaces that make a lot of data coming from different sources available to the user in a transparent way. The Semantic Web technologies seem to facilitate the data integration problem on the Web by providing the necessary languages to describe the data semantics. Very often the Web user browses pages that he will like to view again at a later time. The present browsing history mechanisms included in Web browsers proved to be insufficient for an adequate retrieval of already seen information. A semantical organization of the previously visited pages can improve the process of retrieving previously seen data. There is an increasing demand to make WIS personalizable so that these systems better deal with the user interests. WIS design methodologies do propose adaptation techniques in order to realize WIS personalization. Despite the fact that some of these adaptation techniques are very similar (or even the same) in different methodologies, the notations to specify WIS personalization aspects are quite different. By defining a reference model for specifying WIS personalization one could improve the reuse of the personalization specifications and also enable a seamless translation between different specific personalization specifications. The above issues are some of the topics that are tackled in the workshop papers. We hope that we did raise the readers’ interest so that they will have a close look at the papers and possibly contribute to the fascinating and challenging area of WIS modeling