Abstract The goal of personalization in information retrieval is to tailor the search engine results to the specific goals, preferences and general interests of the users. We propose a novel model for both user profiling and document ranking that consider the user interests as sources of evidence in order to tune the accuracy of the documents returned in response to... The goal of personalization in information retrieval is to tailor the search engine results to the specific goals, preferences and general interests of the users. We propose a novel model for both user profiling and document ranking that consider the user interests as sources of evidence in order to tune the accuracy of the documents returned in response to the user query. User profiling is performed by managing the user search history using statistical based operators in order to highlight the user short-term interests seen as surrogates for building the long-term ones. The document ranking model’s foundation comes from influence diagrams which are extension of Bayesian graphs, dedicated to decision-making problems. Hence, query evaluation is carried out as an inference process that aims at computing an aggregated utility of a document by considering its relevance to the query but also the corresponding utility with regard to the user’s topics of interest. Experimental results using enhanced TREC collections indicate that our personalized retrieval model is effective. Read More Read Less

Abstract An effect of the growing importance of the Semantic Web used for sharing knowledge over the Internet was the development and publishing of many ontologies in different domains. This led to the need of developing mechanisms for capturing the semantics of the ontologies. In this paper, we introduce the OntoNL Semantic Relatedness Measure, a fully automated way of measuring, in... An effect of the growing importance of the Semantic Web used for sharing knowledge over the Internet was the development and publishing of many ontologies in different domains. This led to the need of developing mechanisms for capturing the semantics of the ontologies. In this paper, we introduce the OntoNL Semantic Relatedness Measure, a fully automated way of measuring, in an asymmetric way, semantic relatedness between concepts of domain ontologies. We have developed metrics to guide the automation of the procedure by using feedback from an extensive evaluation with human subjects. We conclude with an application based evaluation using the OntoNL Framework as the application platform, a Natural Language Interface Generator for Knowledge Repositories. Read More Read Less

Abstract The huge number of available documents on the Web makes finding relevant ones a challenge. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. Especially, the ambiguities... The huge number of available documents on the Web makes finding relevant ones a challenge. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. Especially, the ambiguities of natural languages and abstract concepts are handled inadequately by full-text search engines. Ontologies provide a solution to these problems. They can help a user to find documents related to a specific domain. This paper proposes a new retrieval system based on ontologies. This system integrates results from traditional full-text engines, and thus supports a gradual transition from classical full-text search engines to ontology-based ones. Read More Read Less

Abstract The concept of Virtual Organisation (VO) is a natural outcome of networks evolution and collaborative work tools growth. In the VIVACE and TSCP projects, we have studied the different issues when setting VOs up. In this paper, we expose requirements and characteristics of VOs through a use case, which was proposed by these two consortiums. Then, we present a secured... The concept of Virtual Organisation (VO) is a natural outcome of networks evolution and collaborative work tools growth. In the VIVACE and TSCP projects, we have studied the different issues when setting VOs up. In this paper, we expose requirements and characteristics of VOs through a use case, which was proposed by these two consortiums. Then, we present a secured collaborative environment, which combines attribute based access control models, privilege management infrastructure and identity federation, we have deployed to deal with VO security constraints. This architecture allows organisations to externalise processes such as authenticating remote users to their partners (the users’ home organisations). The establishment of such a decentralised management solution implies these organisations to be sufficiently mature to deal with such delegated tasks. We consider the maturity of the security practices deployed within each organisation to choose the trustee organisations between the potential partners. We provide a tool that helps organisations to evaluate their maturity. Read More Read Less

Abstract This paper describes the basis of citation auctions that are introduced as a new approach to selecting scientific papers for publication. Unlike the state of the art in paper selection that relies on peer reviews, our main idea is to use an auction in which bids consist of the number of citations that an author expects to receive if the... This paper describes the basis of citation auctions that are introduced as a new approach to selecting scientific papers for publication. Unlike the state of the art in paper selection that relies on peer reviews, our main idea is to use an auction in which bids consist of the number of citations that an author expects to receive if the paper is published. Hence, a citation auction is the selection process itself, and no reviewers are involved. The benefits of the proposed approach are two-fold. First, the cost of refereeing will be either totally eliminated or significantly reduced, because the process of citation auction does not need prior understanding of the paper’s content to judge the quality of its contribution. Additionally, the method does not prejudge the content of the paper, so it will increase the openness of publications to new ideas. Second, scientists will be much more committed to the quality of their submitted papers, paying close attention to distributing and explaining their papers in detail to maximize the number of citations that the paper receives when published. Sample analyses of the number of citations collected via Google scholar for papers published in years 1999-2004 in a series of proceedings, and in years 2003-2005 in a series of conferences (in a totally different discipline) are provided. Finally, a simple simulation of an auction is given to outline the behaviour of the citation auction approach. Read More Read Less

Abstract More than 99% of European enterprises are SMEs (Small and Medium-sized Enterprises). While in the current market situation collaboration is evolving to an indispensable key factor of success, research is yet to produce results which can be used by SMEs. This paper introduces an interoperability approach in the context of the European Commius Project which enables SMEs collaborate easily on... More than 99% of European enterprises are SMEs (Small and Medium-sized Enterprises). While in the current market situation collaboration is evolving to an indispensable key factor of success, research is yet to produce results which can be used by SMEs. This paper introduces an interoperability approach in the context of the European Commius Project which enables SMEs collaborate easily on the level of process interoperability. The Commius solution will dock onto existing E-Mail structures and enrich incoming E-Mails with additional information dependant upon its content and provide recommendations of expedient further steps to process the E-Mail. A first picture of the Commius process interoperability layer architecture will be drawn. Furthermore proposals to adapt Commius to the specific processes every SME has, in a simple way, are being exposed. Read More Read Less

Abstract In this work we present APA Labs, a generic framework for visualizing the news article domain. APA Labs is a web-based platform enabling retrieval and analysis of news repositories provided by the Austrian Press Agency. APA Labs is designed as a rich internet application combined with a modular system of interactive visualizations. News articles are analyzed using domain specific named... In this work we present APA Labs, a generic framework for visualizing the news article domain. APA Labs is a web-based platform enabling retrieval and analysis of news repositories provided by the Austrian Press Agency. APA Labs is designed as a rich internet application combined with a modular system of interactive visualizations. News articles are analyzed using domain specific named entity extraction methods combined with language specific heuristics. The proposed methods were subject to an evaluation procedure outlined in this contribution. This article illustrates the domain, the underlying concepts and implementation details. Several visualization modules are presented and an outlook on planned modules is given. Being online for around six months the community feedback as well as the easy integration of new modules shows the success of the underlying concept and the platform itself. Read More Read Less

Abstract The textual content of company annual reports has proven to contain predictive indicators for the company future performance. This paper addresses the general re search question of evaluating the effectiveness of applying machine learning and text mining techniques to building predictive models with annual reports. More specifically, we focus on these two questions: 1) the feasibility of build ing ranking... The textual content of company annual reports has proven to contain predictive indicators for the company future performance. This paper addresses the general re search question of evaluating the effectiveness of applying machine learning and text mining techniques to building predictive models with annual reports. More specifically, we focus on these two questions: 1) the feasibility of build ing ranking models with annual reports to rank future firm performance and 2) the effect of integrating meta seman tic features to help improve and support our prediction. We compare models built with different ranking algorithms and document models. We evaluate our models with a simulated portfolio. Our results show significantly positive average returns over 5 years with a power law trend as we increase the ranking threshold. Adding meta features to document model has shown to improve ranking performance. The SVR & Metaaugemented model outperforms the others and pro vides potential for explaining the textual factors behind the prediction. Read More Read Less