Improving Ontology Recommendation and Reuse in WebCORE by Collaborative Assessments

In this work, we present an extension of CORE [8], a tool for Collaborative Ontology Reuse and Evaluation. The system receives an informal description of a specific semantic domain and determines which ontologies from a repository are the most appropriate to describe the given domain. For this task, the environment is divided into three modules. The first component receives the problem description as a set of terms, and allows the user to refine and enlarge it using WordNet. The second module applies multiple automatic criteria to evaluate the ontologies of the repository, and determines which ones fit best the problem description. A ranked list of ontologies is returned for each criterion, and the lists are combined by means of rank fusion techniques. Finally, the third component uses manual user evaluations in order to incorporate a human, collaborative assessment of the ontologies. The new version of the system incorporates several novelties, such as its implementation as a web application; the incorporation of a NLP module to manage the problem definitions; modifications on the automatic ontology retrieval strategies; and a collaborative framework to find potential relevant terms according to previous user queries. Finally, we present some early experiments on ontology retrieval and evaluation, showing the benefits of our system

Development of the Information Society in Czech Republic, Poland and Slovakia

The article is presenting facts about the politics carried on the EU concerning development of the information society in Czech Republic, Poland and Slovakia - countries that in 2004 became members of the EU. Enlargement of the EU structures allowed for more dynamic development of these countries in the information society context. The situation of each country was presented by indicators describing the household and the community situation in information society. Indicators was gained from Eurostat system. The universality of these indicators lets to the assessment of the level and dynamics of development in relation to the EU average. Comparison of Poland and its southern neighbors allows also to observe changes that occur and may allow better progress in this field.Artykul prezentuje dane na temat prowadzonej w UE polityki w zakresie rozwoju spoleczeństwa informacyjnego w Czechach, Polsce i Slowacji, które staly się czlonkami UE w 2004 roku. Rozszerzenie struktur unijnych pozwolilo na zdynamizowanie rozwoju tych krajów w zakresie spoleczeństwa informacyjnego. Sytuację poszczególnych krajów zaprezentowano przy pomocy wskażników opisujących gospodarstwa domowe oraz spoleczność pochodzące z Eurostatu. Powszechność tych wskażników pozwala na ocenę dynamiki rozwoju oraz poziomu tego rozwoju w odniesieniu do wartości średniej w UE. Porównanie Polski oraz jej poludniowych sąsiadów pozwolić ma również na dostrzeżenie przemian, które zachodzą i mogą pozwolić na lepszy postęp w tej dziedzinie

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

Finding iteration patterns in dynamic Web page authoring

The final publication is available at Springer via http://dx.doi.org/10.1007/11431879_10Revised Selected Papers of the Joint Working Conferences EHCI-DSVIS 2004, Hamburg, Germany, July 11-13, 2004Most of the current WWW is made up of dynamic pages. The development of dynamic pages is a difficult and costly endeavour, out-of-reach for most users, experts, and content producers. We have developed a set of techniques to support the edition of dynamic web pages in a WYSIWYG environment. In this paper we focus on specific techniques for inferring changes to page generation procedures from users actions on examples of the pages generated by these procedures. More specifically, we propose techniques for detecting iteration patterns in users’ behavior in web page editing tasks involving page structures like lists, tables and other iterative HTML constructs. Such patterns are used in our authoring tool, DESK, where a specialized assistant, DESK-A, detects iteration patterns and generates, using Programming by Example, a programmatic representation of the user’s actions. Iteration patterns help obtain a more detailed characterization of users’ intent, based on user monitoring techniques, that is put in relation to application knowledge automatically extracted by our system from HTML pages. DESK-A relieves end-users from having to learn programming and specification languages for editing dynamic-generated web pages.The work reported in this paper is being supported by the Spanish Ministry of Science and Technology (MCyT), project number TIC2002-194

Information and Communication Technology (ICT) and International Business Travel: Mobility Allies?

Like forecasts about the paperless office, technological solutions to the problem of international business travel continue to be deferred. As with the increased use of office paper, international business travel is defying predictions of its decline. There is growing evidence to suggest that business sectors which seem ideally placed to substitute information and communication technology (ICT) for travel, are actually generating more physical travel than other sectors. This paper develops a case study of the Irish software industry to exemplify why international travel is not diminishing in importance how and the ICT and business travel relationship is changing in this sector. The paper presents research findings that suggest that a cycle of substitution, generation and modification relationships have occurred as mobility interdependencies have developed.Peer Reviewe

Ca impurity in small mixed 4^4He-3^3He clusters

The structure of small mixed helium clusters doped with one calcium atom has been determined within the diffusion Monte Carlo framework. The results show that the calcium atom sits at the $^4$He-$^3$He interface. This is in agreement with previous studies, both experimental and theoretical, performed for large clusters. A comparison between the results obtained for the largest cluster we have considered for each isotope shows a clear tendency of the Ca atom to reside in a deep dimple at the surface of the cluster for $^4$He clusters, and to become fully solvated for $^3$He clusters. We have calculated the absorption spectrum of Ca around the $4s4p \leftarrow 4s^2$ transition and have found that it is blue-shifted from that of the free-atom transition by an amount that depends on the size and composition of the cluster.Comment: 24 pages, 11 figures. Accepted on Journal of Chemical Physic

Workshop on Learning and Evaluating Recommendations with Impressions (LERI)

Recommender systems typically rely on past user interactions as the primary source of information for making predictions. However, although highly informative, past user interactions are strongly biased. Impressions, on the other hand, are a new source of information that indicate the items displayed on screen when the user interacted (or not) with them, and have the potential to impact the field of recommender systems in several ways. Early research on impressions was constrained by the limited availability of public datasets, but this is rapidly changing and, as a consequence, interest in impressions has increased. Impressions present new research questions and opportunities, but also bring new challenges. Several works propose to use impressions as part of recommender models in various ways and discuss their information content. Others explore their potential in off-policy-estimation and reinforcement learning. Overall, the interest of the community is growing, but efforts in this direction remain disconnected. Therefore, we believe that a workshop would be useful in bringing the community together

Impressions in Recommender Systems: Present and Future

Impressions are a novel data source providing researchers and practitioners with more details about user interactions and their context. In particular, an impression contain the items shown on screen to users, alongside users' interactions toward such items. In recent years, interest in impressions has thrived, and more papers use impressions in recommender systems. Despite this, the literature does not contain a comprehensive review of the current topics and future directions. This work summarizes impressions in recommender systems under three perspectives: recommendation models, datasets with impressions, and evaluation methodologies. Then, we propose several future directions with an emphasis on novel approaches. This work is part of an ongoing review of impressions in recommender systems

Characterizing Impression-Aware Recommender Systems

Impression-aware recommender systems (IARS) are a type of recommenders that learn user preferences using their interactions and the recommendations (also known as impressions) shown to users. The community’s interest in this type of recommenders has steadily increased in recent years. To aid in characterizing this type of recommenders, we propose a theoretical framework to define IARS and classify the recommenders present in the state-of-the-art. We start this work by defining core concepts related to this type of recommenders, such as impressions and user feedback. Based on this theoretical framework, we identify and define three properties and three taxonomies that characterize IARS. Lastly, we undergo a systematic literature review where we discover and select papers belonging to the state-of-the-art. Our review analyzes papers under the properties and taxonomies we propose; we highlight the most and least common properties and taxonomies used in the literature, their relations, and their evolution over time, among others

Personalized information retrieval based on context and ontological knowledge

The article has been accepted for publication and appeared in a revised form, subsequent to peer review and/or editorial input by Cambridge University PressExtended papers from C&O-2006, the second International Workshop on Contexts and Ontologies, Theory, Practice and Applications1 collocated with the seventeenth European Conference on Artificial Intelligence (ECAI)Context modeling has been long acknowledged as a key aspect in a wide variety of problem domains. In this paper we focus on the combination of contextualization and personalization methods to improve the performance of personalized information retrieval. The key aspects in our proposed approach are a) the explicit distinction between historic user context and live user context, b) the use of ontology-driven representations of the domain of discourse, as a common, enriched representational ground for content meaning, user interests, and contextual conditions, enabling the definition of effective means to relate the three of them, and c) the introduction of fuzzy representations as an instrument to properly handle the uncertainty and imprecision involved in the automatic interpretation of meanings, user attention, and user wishes. Based on a formal grounding at the representational level, we propose methods for the automatic extraction of persistent semantic user preferences, and live, ad-hoc user interests, which are combined in order to improve the accuracy and reliability of personalization for retrieval.This research was partially supported by the European Commission under contracts FP6-001765 aceMedia and FP6-027685 MESH. The expressed content is the view of the authors but not necessarily the view of the aceMedia or MESH projects as a whole