Semantic Interoperability in the BRITE project: Ontologies as a Tool for Collaboration, Cooperation and Knowledge Management Timo Herborn1 , Ansgar Mondorf1 , Babak Mougouie2 , and Maria A. Wimmer1 1
University of Koblenz-Landau, Institute for Information Systems Research, Universitaetsstrasse 1, 56070 Koblenz, Germany {herborn,mondor,wimmar}@uni-koblenz.de 2 DFKI GmbH, Knowledge Management Department Kaiserslautern, Germany
[email protected]
Abstract. Ontologies have been investigated for a while and are being studied as an instrument to enable cross-organizational semantic interoperability. The project BRITE (Business Register Interoperability Throughout Europe) aims at exploring ontologies as an instrument to effectively enable European Business Registers (BRs) to respond to changes imposed on them by European Union laws and new market requirements. In BRITE, ontologies are seen as a key instrument and technology to dissolve administrative, technical, cultural and lingual barriers of BRs on one hand, and as means to provide semantic interoperability on the other hand. The paper shows various ontology components of BRITE. It defines the inter-relation among these components and focuses on the domain ontology functionalities. We conclude with a critical reflection and valuable lessons learnt. Keywords:eGovernment, ontology, application of ontologies, interoperability, semantic interoperability, lessons learnt.
The 16th International Conference on Cooperative Information Systems (CoopIS 2008). Monterrey, Mexico, 12-14 November, 2008.
Optimization Algorithms to Find Most Similar Deductive Consequences (MSDC) Babak Mougouie1,2 1
2
University of Trier Department of Business Information Systems II Trier, Germany DFKI GmbH, Knowledge Management Department Kaiserslautern, Germany
[email protected]
Abstract. Finding most similar deductive consequences, MSDC, is a new approach which builds a unified framework to integrate similaritybased and deductive reasoning. In this paper we introduce a new formulation OP-MSDC(q) of MSDC which is a mixed integer optimization problem. Although mixed integer optimization problems are exponentially solvable in general, our experimental results show that OP-MSDC(q) is surprisingly solved faster than previous heuristic algorithms. Based on this observation we expand our approach and propose optimization algorithms to find the k most similar deductive consequences k-MSDC.
The 9th European Conference on Case-Based Reasoning (ECCBR 2008), Trier, Germany, 1-4 September, 2008.
DOLCE ergo SUMO: On Foundational and Domain Models in SWIntO (SmartWeb Integrated Ontology) Daniel Oberle,1,7 Anupriya Ankolekar,1 Pascal Hitzler,1 Philipp Cimiano,1 2 Michael Sintek, Malte Kiesel,2 Babak Mougouie,2 Shankar Vembu,2 Stephan Baumann,2 3 Massimo Romanelli, Paul Buitelaar,3 Ralf Engel,3 Daniel Sonntag,3 Norbert Reithinger,3 4 Berenike Loos, Robert Porzel,4 Hans-Peter Zorn,4 Vanessa Micelli,4 Christian Schmidt,5 Moritz Weiten,5 Felix Burkhardt, and6 Jianshen Zhou6 1
Institut AIFB, Universit¨ at Karlsruhe, Germany,
[email protected] 2 DFKI KM, Kaiserslautern, Germany,
[email protected] 3 DFKI IUI & LT, Saarbr¨ ucken, Germany,
[email protected] 4 European Media Lab (EML), Heidelberg, Germany,
[email protected] 5 ontoprise GmbH, Karlsruhe, Germany,
[email protected] 6 T-Systems, Berlin, Germany,
[email protected] 7 now at: SAP Research, CEC Karlsruhe, Germany,
[email protected]
Abstract. Increased availability of mobile computing, such as personal digital assistants (PDAs), creates the potential for constant and intelligent access to up-to-date, integrated and detailed information from the Web, regardless of ones actual geographical position. Intelligent questionanswering requires the representation of knowledge from various domains, such as the navigational and discourse context of the user, potential user questions, the information provided by Web services and so on, for example in the form of ontologies. Within the context of the SmartWeb project, we have developed a number of domain-specific ontologies that are relevant for mobile and intelligent user interfaces to open-domain question-answering and information services on the Web. To integrate the various domain-specific ontologies, we have developed a foundational ontology, the SmartSUMO ontology, on the basis of the DOLCE and SUMO ontologies. This allows us to combine all the developed ontologies into a single SmartWeb Integrated Ontology (SWIntO) having a common modeling basis with conceptual clarity and the provision of ontology design patterns for modeling consistency. In this paper, we present SWIntO, describe the design choices we made in its construction, illustrate the use of the ontology through a number of applications, and discuss some of the lessons learned from our experiences.
Journal of Web Semantics: Sci. Services Agents WWW, pp. 156-174, 2007.
Finding Similar Deductive Consequences – A New Search-Based Framework for Unified Reasoning from Cases and General Knowledge Ralph Bergmann and Babak Mougouie University of Trier Department of Business Information Systems II 54294 Trier, Germany {bergmann,mougouie}@wi2.uni-trier.de
Abstract. While reasoning with cases is usually done in a similaritybased manner, additional general knowledge is often represented in rules, constraints, or ontology definitions and is applied in a deductive reasoning process. This paper presents a new view on the combination of deductive and similarity-based reasoning, which is embedded in the CBR context. The basic idea is to view general knowledge and cases as a logical theory of a domain. Similarity-based reasoning is introduced as search for the most similar element in the deductive closure of the domain theory. We elaborate this approach and introduce several related search algorithms, which are analyzed in an experimental study. Further, we show how several previous approaches for using general knowledge in CBR can be mapped to our new view.
LNCS 4106, Advances in Case-Based Reasoning, 2006, Springer. The 8th European Conference on Case-Base Reasoning (ECCBR 2006) Fethiye, Turkey, pp. 271-285, 4-7 September 2006.
Polynomial Algorithms for MPSP using Parametric Linear Programming Babak Mougouie Max-Planck Institut f¨ ur Informatik, Stuhlsatzenhausweg 85, 66123 Saarbr¨ ucken, Germany
[email protected]
Abstract. The multiprocessor scheduling problem(MPSP), P |prec, pj = 1|Cmax , is known to be NP-complete. The problem is polynomially solvable, however, if the precedence relations are of the intree(outtree) type, P |intree(outtree), pj = 1|Cmax , or if the number of processors is two, P 2|prec, pj = 1|Cmax . In this paper, we introduce a parametric linear program which gives a lower bound for the makespan of MPSP and retrieves the makespans of the two polynomially solvable problems.
In: Wolfgang Lenski, editor, Logic versus Approximation, Essays Dedicated to Michael M. Richter on the Occasion of His 65th Birthday, pp. 33-42, LNCS 3075, SpringerVerlag. 2004.
Generalized Cases, Similarity and Optimization Babak Mougouie1 and Michael M. Richter2 1
Max-Planck Institut f¨ ur Informatik, Saarbr¨ ucken, Germany
[email protected] 2 Informatics Department, University of Kaiserslautern, Kaiserslautern, Germany
[email protected]
Abstract. The technique of generalized cases in order to deal with large problem spaces is investigated. We restrict ourselves to the main problem of determining the similarity between a query and a generalized case; this is translated into a real valued optimization problem. Special difficulties are provided by non-linear constraints and nondifferentiable similarity functions for which classical optimization techniques had to be extended.
In: D. Hutter, and W. Stephan, editors, Deduction and beyond. LNAI 2605, SpringerVerlag. 2003.
Diversity-Conscious Retrieval from Generalized Cases: A Branch and Bound Algorithm Babak Mougouie1 , Michael M. Richter2 , and Ralph Bergmann3 1
Max-Planck Institute for Computer Science, Stuhlsatzenhausweg 85, 66123 Saarbr¨ ucken, Germany
[email protected] 2 University of Kaiserslautern, Artificial Intelligence and Knowledge-Based Systems Group PO-Box 3049, 67653 Kaiserslautern, Germany
[email protected] 3 University of Hildesheim, Data- and Knowledge Management Group PO-Box 101363, 31113 Hildesheim, Germany
[email protected]
Abstract. Recommendation systems offer the most similar point cases to a target query. Among those cases similar to the query, some may be similar and others dissimilar to each other. Offering only the most similar cases wrt. the query leads to the well known problem that the customers may have only a few number of choices. To address the problem of offering a diverse set of cases, several approaches have been proposed. In a different line of CBR research, the concept of generalized cases has been systematically studied, which can be applied to represent parameterizable products. First approaches to retrieving the most similar point cases from a case base of generalized cases have been proposed. However, until now no algorithm is known to retrieve a diverse set of point cases from a case base of generalized cases. This is the topic of this paper. We present a new branch and bound method to build a retrieval set of point cases such that its diversity is sufficient and each case in the retrieval set is a representative for a set of similar point cases.
In: Kevin D. Ashley, and Derek Bridge, editors, 5th International Conference on Case-Based Reasoning (ICCBR 2003), Trondheim, Norway, 23-26 June 2003. LNAI 2689, pp. 319-331, Springer-Verlag. 2003.
Similarity Assessment for Generalizied Cases by Optimization Methods Babak Mougouie1 and Ralph Bergmann2 1
2
Max-Planck Institut f¨ ur Informatik, Saarbr¨ ucken, Germany
[email protected] University of Hildesheim, Data- and Knowledge Management Group PO-Box 101363, D-31113 Hildesheim, Germany
[email protected]
Abstract. Generalized cases are cases that cover a subspace rather than a point in the problem-solution space. Generalized cases can be represented by a set of constraints over the case attributes. For such representations, the similarity assessment between a point query and generalized cases is a difficult problem that is addressed in this paper. The task is to find the distance (or the related similarity) between the point query and the closest point of the area covered by the generalized cases, with respect to some given similarity measure. We formulate this problem as a mathematical optimization problem and we propose a new cutting plane method which enables us to rank generalized cases according to their distance to the query.
In: S. Craw, and A. Preece, editors, The 6th European Conference (ECCBR 2002) Aberdeen, Scotland, UK, 4-7 September 2002, volume 2416 of LNAI, pp. 249-263, Springer, 2002.
