SIG KM NEWSLETTER Issue December 2006 Newsletter of the German Special Interest Group on Knowledge Management www.fgwm.de Subscribe or unsubscribe via http://www.fgwm.de Send contributions to: 'bergmann' or 'minor' at 'uni-trier.de' TABLE OF CONTENTS 1. Call for Papers: Seventh International Conference on Case-Based Reasoning (ICCBR'07) 2. Call for Contributions: KI Special Issue on Experience Management (in German) 3. Call for Papers: AAAI-07 Nectar Track 4. Call for Anecdotes: AI Magazine Special Issue on What Went Wrong and Why (submission deadline: January 1, 2007) 5. Call for Papers: 5th IAPR International Conference on Machine Learning and Data Mining (MLDM'07, submission deadline: January 9, 2007) 6. Call for Book Chapters: Soft Computing Applications in Business ......................................................................... *sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm* ......................................................................... ICCBR 2007 Call for papers Seventh International Conference on Case-Based Reasoning Belfast, Northern Ireland, 13-16 August 2007 www.iccbr.org/iccbr07 ICCBR and ECCBR are the premier international meetings on case-based reasoning. While ECCBR conferences are always held in Europe, previous ICCBR conferences have been held in Chicago, USA (2005), Trondheim, Norway (2003), Vancouver, Canada (2001), Seeon Monastery, Germany (1999), Providence, Rhode Island, USA (1997), and Sesimbra, Portugal (1995). The next ICCBR will be held in Belfast, Northern Ireland from the 13th to the 16th of August. In order to expand the frontiers of CBR as a scientific field, we would like to emphasize the connections between CBR and related areas, and to explore new problems and industrial solutions. For this reason, we will combine an industry program with the scientific and workshop programs. The conference will bring two keynote speakers from outside the community, who will help us to cross current boundaries of CBR research towards intelligent databases and bioinformatics. Larry Kerschberg from George Mason University will talk about CBR and Databases and Larry Hunter will bring new ideas on how to explore CBR for bioinformatics. The conference will bring two invited speakers from the CBR community. Eva Armengol will talk about machine learning and David W. Aha will discuss problems concerning the perceived lack of theoretical foundations in CBR by funding agencies. Important Dates ============ Submission deadline: 14 February 2007 Notification of acceptance: 05 April 2007 Camera ready copy due: 05 May 2007 Submission Topics ============== The ICCBR'07 Program Committee invites submissions of original theoretical research, applied research, and deployed application papers on all aspects of Case-Based Reasoning. Example submission areas include, but are not limited to: - Case-based reasoning foundations - Conversational case-based reasoning - Textual case-based reasoning - Distributed case-based reasoning - Case-based reasoning and uncertainty - Case-based reasoning in design, diagnosis, health, law, education - Knowledge management in case-based reasoning, case and experience-based knowledge management - Case-based recommender systems - Fielded applications of case-based reasoning - Case and knowledge representation, acquisition, modeling, visualization, maintenance and management for CBR - CBR system design issues (e.g., indexing, retrieval, similarity assessment and adaptation) - Collaborative agent architectures involving CBR - Analogical reasoning, cognitive models, and creative reasoning approaches based on CBR - Formal, empirical, and psychological evaluations of CBR models and systems - Lazy-learning, instance-based learning and case-based learning - Case-based approaches to scheduling, design and robot navigation - Adaptive interfaces, user modeling, customization and personalization using CBR - CBR and knowledge discovery, data mining, text mining - CBR software reuse and engineering redesign - Explanations, Context, and confidence in CBR - Peer-to-Peer Networks and CBR - CBR in the Semantic Web Proceedings ========== All accepted papers will appear in the conference proceedings published by Springer Verlag in the Lecture Notes in Artificial Intelligence series. Review Criteria =========== Each submission must be identified as theoretical/methodological research, applied research, or deployed application paper and will be reviewed using criteria appropriate to its category. Because we understand that some papers may be in the borderline between two categories, we encourage authors to enter a second category if they feel appropriate. The criteria are as follows: Paper Category: Theoretical/Methodological research paper Review Criteria: Scientific significance; originality; technical quality; and clarity Paper Category: Applied research paper Review Criteria: Significance for advancing applications or promise for innovative commercial development; originality; technical quality; and clarity Paper Category: Deployed application paper Review Criteria: Demonstrated practical, social, environmental or economic significance; originality; treatment of issues of engineering, management & user acceptance; and clarity. Submission Format ============== Papers MUST be submitted in Springer LNCS format, which is the format required for the final camera ready copy, with a maximum of 15 pages. Authors' instructions along with LaTeX and Word macro files are available on the web: http://www.springer.com/east/home/computer/lncs?SGWID=5-164-7-72376-0 Authors of accepted papers are required to transfer their copyrights to Springer. All submissions are required to be in electronic format. Submission Procedure =============== Authors must submit a full paper by 14 February 2007. Submission instructions will be made available here: http://www.iccbr.org/iccbr07/submission.html Multiple Submission Policy ================== Papers submitted to other conferences or journals must state this fact. If a paper will appear in another conference or journal, it must be withdrawn from ICCBR'07 before 30 March 2007. This restriction does not apply to papers appearing in proceedings of specialized workshops. Author Registration Policy ================= In order for a paper to appear in the proceedings, at least one of the authors must register for the conference by the deadline for camera-ready copies (05 May 2007). People ====== Program Chairs: Michael Richter, University of Kaiserslautern, Germany (richter at informatik.uni-kl.de) Rosina Weber, Drexel University, USA (rosina.weber at drexel.edu) Conference Chair: David Patterson, University of Ulster, Northern Ireland (wd.patterson at ulster.ac.uk) Workshop Program Chairs: David Wilson, University of North Carolina, USA (davils at uncc.edu) Deepak Khemani, IIT Madras, India (khemani at iitm.ac.in) Industry Program Chair: Thomas Roth-Berghofer, DFKI, Germany (Thomas at Roth-Berghofer.de) For the PC members see http://www.iccbr.org/iccbr07/call.html ......................................................................... *sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm* ......................................................................... KI-Schwerpunkt "Erfahrungsmanagement" Erfahrungen sind nicht nur f.AN|r Unternehmen ein wichtiger Faktor zur Entscheidungsfindung und BewNdltigung neuer Aufgaben. Trotzdem wird das Erfahrungswissen in Firmen oft nur unzureichend dokumentiert und nicht effektiv in entsprechende Prozesse eingebracht. Systematische AnsNdtze des Erfahrungsmanagements (EM) sollen diesen Missstand beheben und bedienen sich dazu der Methoden der KI zum Beispiel aus den Bereichen WissensreprNdsentation, Suche und Inferenz. Um die Anwendbarkeit solcher Methoden sicher zu stellen, werden mittlerweile auch schwach strukturierte Verfahren bzw. Technologien damit kombiniert, zum Beispiel Fallbasiertes SchlieN_en und Wikis. Trotzdem sind allgemeine Suchmaschinen nach wie vor die meistgenutzte Methode zum Auffinden von Erfahrungswissen und es bleiben immer noch die Fragen: - Welche Vorteile bringen intelligente Verfahren gegen.AN|ber Suchmaschinen wie Google? - Wie sollten moderne EM-Systeme entworfen und eingesetzt werden? - Was charakterisiert eigentlich Erfahrungswissen im Unterschied zu anderen Wissensarten? Das Schwerpunktthema "Erfahrungsmanagement" soll Antworten auf diese und andere Fragen geben. Wir bitten um Einreichung von Beitr.ANdgen zu folgenden Themen: - Integration von Lernzyklen und Feedback-Mechanismen im EM - Prozessmodelle zur Erfassung, Integration, Verbreitung und Maintenance von Erfahrungswissen - Evaluation von Erfahrungsmanagement Ans.ANdtzen, z. B. o Vergleich von KI-Ans.ANdtzen und schwach strukturierten AnsNdtzen wie Wikis, Blogs und Community Newsgroups - Spezielle Technologien und Methodologien zur Unterst.AN|tzung des EM z. B. o Fallbasiertes Schlie.AN_en o Agentenorientierte Techniken o Workflow Management bzw. Process Enactment Ans.ANdtze o Organizational Memories - EM-Anwendungen z. B. f.AN|r o Management von "Best Practices" und "Lessons Learned" o Dokumentenmanagement o Medizinische Diagnose und Erfassung, Interventionsmedizin - EM in Netzwerken, Communities und Folksonomies - Context-Awareness und ambientes EM - Ganzheitliches EM, psychologische und soziokulturelle Aspekte Interessierte Autoren werden gebeten, Beitr.ANdge in den Rubriken Fachbeitrag, Projekt, Zur Diskussion und KI-Markt bis 19. Januar 2007 einzureichen an Mirjam Minor, Univ. Trier, minor "at" uni-trier.de und Martin Schaaf, Univ. Hildesheim, schaaf "at" iis.uni-hildesheim.de Weitere Infos siehe www.kuenstliche-intelligenz.de ......................................................................... *sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm* ......................................................................... AAAI-07 will again include the Nectar track, whose goal is to make the most significant AI results presented in sister conferences in the last two years available to a broad AI audience. The Nectar (new scientific and technical advances in research) track will consist of papers that are based on important results that have already been published in the proceedings of at least one major specialized conference in 2005 and 2006, as either a single paper or a series of papers. Examples of such conferences include AAMAS, AIIDE, ALIFE, ACL, CEC, CogSci, CP, FUZZ-IEEE, GECCO, ICAPS, ICCBR, ICML, ICRA, IEEE CEC, IJCNN, IROS, ISWC, IUI, KCAP, KR, NIPS, RSS, SAT, UAI and WCCI. Examples of conferences in related fields with relevance to AI are ALife, CIKM, COLT, KDD, PODS, ICDTSIGIR, SIGMOD, VLDB, and WWW. Papers that report on the application of AI techniques in other fields, for example bioinformatics, may also serve as the basis for Nectar papers. Authors of application papers, however, are advised that they may find the conference on innovative applications of AI (IAAI) a more appropriate venue for reaching the AI community since those papers can be longer and thus provide a clearer application setting in which to describe the work. Papers that have appeared in either AAAI or IJCAI cannot serve as the basis for Nectar papers since they have already been presented to the entire AI community. One important goal of the track is to offer young researchers the opportunity to learn about areas with which they may not already be familiar. Another goal is to encourage the sort of cross-disciplinary AI work that has historically been supported by AAAI. We solicit short submissions of up to four pages. Each submission should focus on a major result that has already been published in one or more venues as described above. A Nectar paper needs to clarify the relationship of the paper to any other AAAI-07 submissions by the authors and cannot overlap with them substantially. The Nectar paper should cite the previous publication(s) and will typically devote no more than one or two pages to summarizing the core results. The remainder of the paper should be devoted to putting the results, as well as the problem they solve, into a context that is meaningful to a wide AI audience. AAAI Nectar track papers will be presented as short talks or posters at AAAI-07. The papers will also be published in the conference proceedings. Submitted papers will be reviewed according to: (1) significance of the result to the broad goals of AI, (2) potential for the result to influence work in other areas of AI, and (3) clarity of the presentation to a wide AI audience. Although papers will describe previously published results, the paper itself must be original. Authors of accepted papers will be required to transfer copyright. Papers must be received by February 27, 2007. Decisions on the acceptance of papers will be made by March 29, 2007. For more information, as it becomes available, please see www.aaai.org/Conferences/AAAI/aaai07.php and www.aaai.org/Conferences/AAAI/2007/aaai07nectarcall.php Elaine Rich (University of Texas at Austin), Cochair Sven Koenig (University of Southern California), Cochair ......................................................................... *sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm* ......................................................................... Call for Anecdotes AI Magazine Special Issue on What Went Wrong and Why Bugs, glitches, and failures pepper the research and development process. They identify both problems and opportunities by revealing assumptions, clarifying design flaws, and exposing misconceptions. Errors are often more informative than successful results, as they demand attention to lessons learned. We believe that every person working in the field of Artificial Intelligence has encountered the beneficial impact of bugs. We are collecting anecdotes that capture such experiences for publication in an upcoming special issue of AI Magazine entitled "What Went Wrong and Why". Authors should submit 400 word descriptions of experiences that link problems to insights/lessons learned. The topics are essentially unconstrained. Problems can include, but are not limited to: unusual observations, odd algorithm behavior, technology/application mismatch, risk to people, products, projects, or corporations, and physical systems failure. The lessons learned may be technical, methodological, commercial, or organizational in nature, and more. The ideal contribution will be crisp, of general interest, and related to some aspect of AI. Humor is a plus. Selected anecdotes will be published as sidebars in the special issue. Please send contributions to Dan Shapiro (dgs at stanford.edu) or Mehmet Goker (mehmet.goker at us.pwc.com) by January 1, 2007 in text, postscript, pdf, or MSWord format. ......................................................................... *sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm* ......................................................................... Call for Papers 5th IAPR International Conference on Machine Learning and Data Mining MLDM.AN42007 July 18 - 20, 2007, Leipzig/Germany Chair Petra Perner Institute of Computer Vision and applied Computer Sciences, IBaI Leipzig/Germany Program Committee Agnar Aamodt NTNU/Norway Nozha Boujemaa INRIA/France Max Bramer University of Portsmouth/UK Horst Bunke University of Bern/Switzerland Krzysztof Cios University of Colorado/USA John Debenham University of Technology/Australia Christoph F. Eick University of Houston/USA Ana Fred Technical University of Lisbon/Portugal Giorgio Giacinto University of Cagliari/Italy Howard J. Hamilton University of Regina/Canada Makato Haraguchi Hokkaido University Sapporo/Japan Tin Kam Ho Bell Laboratories/USA Atsushi Imiya Chiba University/Japan Horace Ip City University/Hong Kong Herbert Jahn Aero Space Center/Germany Abraham Kandel University of South Florida / USA Dimitrios A. Karras Chalkis Institute of Technology/Greece Adam Krzyzak Concordia University, Montreal/Canada Lukasz Kurgan University of Alberta/Canada Longin Jan Latecki Temple University Philadelphia/USA Tao Li Florida International University, USA Brian Lovell University of Queensland/Australia Ryszard Michalski George Mason University/USA Mariofanna Milanova University of Arkansas at Little Rock/USA B.ANiatrice Pesquet-Popescu Ecole Nationale des TNilNicommunications/France Petia Radeva Universitat Autonoma de Barcelona,Spain Fabio Roli University of Cagliari/Italy Gabriella Sanniti di Baja Instituto di Cibernetica/Italy Linda Shapiro University of Washington/USA Sameer Singh Loughborough University/UK Arnold Smeulders University of Amsterdam/NL Patrick Wang Northeastern University/USA Harry Wechsler George Mason University/USA Sholom Weiss IBM Yorktown Heights/USA Djemel Ziou Universit.ANi de Sherbrooke/Canada Aim of the Conference The MLDM.AN42007 conference is the fifth event in a series of Machine Learning and Data Mining meetings, initially organised as international workshops. The aim of MLDMN42007 is to bring together from all over the world researchers dealing with machine learning and data mining, in order to discuss the recent status of the research in the field and to direct its further developments. Basic research papers as well as application papers are welcome. All kinds of applications are welcome, but special preference will be given to multimedia related applications, biomedical applications, and webmining. Paper submissions should be related but not limited to any of the following topics: * association rules * applications of clustering * applications in medicine * aspects of data mining * autoamtic semantic annotation of media content * Bayesian models and methods * conceptional learning and clustering * case-based reasoning and learning * classification and interpretation of images, text, video * classification and model estimation * case-cased reasoning and associative memory * content-based image retrieval * decision trees * deviation and novelty detection * ensemble methods * feature grouping, discretization, selection and transformation * feature learning * frequent pattern mining * high-content analysis of microscopic images in medicine, biotechnology and chemistry * Goodness measures and evaluation (e.g., false discovery rates) * inductive learning including decision tree and rule induction learning * knowledge extraction from text, video, signals and images * learning/adaption of recognition and perception * learning of internal representations and models * learning of appropriate behaviour * learning of action patterns * learning in image pre-processing and segmentation * learning and adaptive control * learning robots * learning in process automation * learning for handwriting recognition * learning of semantic inferencing rules * learning of ontologies * learning of visual ontologies * mining gene data bases and biological data bases * mining images, temporal-spatial data, images from remote sensing * mining text documents * mining structural representations such as log files, text documents and htm- documents * mining financial or stockmarket data * mining images in computer vision * mining images and texture * mining motion from sequence * network analysis and intrusion detection * neural methods * nonlinear function learning and neural net based learning * organisational learning and evolutional learning * probabilistic information retrieval * rule induction and grammars * retrieval methods * real-time event learning and detection * Selection bias * Sampling methods * Selection with small samples * similarity measures and learning of similarity * statistical learning and neural net based learning * support vector machines * subspace methods * statistical and conceptual clustering methods: basics * statistical and evolutionary learning * speech analysis * symbolic learning and neural networks in document processing * time series and sequential pattern mining * text mining * visualization and data mining * video mining Invited Lecture Data Clustering: User$B!G(Bs Dilemma Anil K. Jain Department of Computer Science and Engineering, Michigan State University (USA) Important Dates Deadline for paper submission: January 9, 2007 Notification of acceptance: March 22, 2007 Final paper submission: April 10, 2007 Authors can submit their papers in long or short version: Please Email submissions to info "at" ibai-institut.de. Long Papers Long papers must be formatted in the Springer LNCS format. They should have at most 15 pages. Papers will be reviewed by the program committee. Accepted long papers will appear in the proceedings book "Machine Learning and Data Mining in Pattern Recognition" published by Springer Verlag in the LNAI series. Short Papers Short papers can be used to describe work in progress or project ideas. They should have no more than 5 pages, formatted in Springer LNCS format. Accepted short papers will be presented as posters in the poster session. They will be published in a special poster proceedings book. Special Issue Extended versions of selected papers will be published in a special issue of an international journal after the conference. ......................................................................... *sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm* ......................................................................... Final call for book Chapters The following two books are planned to be published by Springer-Verlag during 2007/2008: (1). Soft Computing Applications in Business (submission deadline: January 15) (2). Soft Computing Applications in Industry (submission closed) We invite book chapter contributions. Please see the website: http://www.bhanuprasad.org/chapters.html for more information. ......................................................................... *sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm*sigkm* .........................................................................