DDDM 2009 - DDDM 2009 The 3rd International Workshop on Domain Driven Data Mining
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Website http://datamining.it.uts.edu.au/dddm09 |
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Category DDDM 2009
Deadline: July 17, 2009 | Date: December 06, 2009
Venue/Country: Florida, U.S.A
Updated: 2010-06-04 19:32:22 (GMT+9)
Call For Papers - CFP
DDDM 2009 The 3rd International Workshop on Domain Driven Data MiningMiami, Florida, USA, December 6, 2009In conjunction with IEEE ICDM'09URL: http://datamining.it.uts.edu.au/dddm09/The Workshop on Domain Driven Data Mining (DDDM) seriesaims to provide a premier forum for sharing findings,knowledge, insight, experience and lessons in tacklingpotential challenges in discovering actionable knowledgefrom complex domain problems, promoting interaction andfilling the gap between academia and business, and drivinga paradigm shift from data-centered hidden pattern miningto domain-driven actionable knowledge delivery in varyingdata mining domains toward supporting smart decision andbusinesses.Following the success of DDDM2007 joint with SIGKDD2007 inthe US and DDDM2008 joint with ICDM2008 in Italy, DDDM2009welcomes theoretical and applied disseminations that makeefforts:- to design next-generation data mining methodology foractionable knowledge discovery and delivery, towardhandling critical issues for KDD to effectively andefficiently contribute to real-world smart businesses andsmart decision and benefit critical domain problems intheory and practice;- to devise domain-driven data mining techniques to bridgethe gap between a converted problem and its actualbusiness problem, between academic objectives andbusiness goals, between technical significance andbusiness interest, and between identified patterns andbusiness expected deliverables, toward strengtheningbusiness intelligence in complex enterprise applications;- to present the applications of domain-driven data miningand demonstrate how KDD can be effectively deployed tosolve complex practical problems; and- to identify challenges and future directions for datamining research and development in the dialogue betweenacademia and industry.TOPICS OF INTERESTThis workshop solicits original theoretical and practicalresearch on the following topics.(1) Methodologies and infrastructure- Domain-driven data mining methodology and projectmanagement- Domain-driven data mining framework, system support andinfrastructure(2) Ubiquitous intelligence- Involvement and integration of human intelligence, domainintelligence, network intelligence, organizationalintelligence and social intelligence in data mining- Explicit, implicit, syntactic and semantic intelligencein data- Qualitative and quantitative domain intelligence- In-depth patterns and knowledge- Human social intelligence and animat/agent-based socialintelligence in data mining- Explicit/direct or implicit/indirect involvement of humanintelligence- Belief, intention, expectation, sentiment, opinion,inspiration, brainstorm, retrospection, reasoning inputsin data mining- Modeling human intelligence, user preference, dynamicsupervision and human-mining interaction- Involving expert group, embodied cognition, collectiveintelligence and consensus construction in data mining- Human-centered mining and human-mining interaction- Formalization of domain knowledge, background and priorinformation, meta knowledge, empirical knowledge in datamining- Constraint, organizational, social and environmentalfactors in data mining- Involving networked constituent information in datamining- Utilizing networking facilities for data mining- Ontology and knowledge engineering and management- Intelligence meta-synthesis in data mining- Domain driven data mining algorithms- Social data mining software(3) Deliverable and evaluation- Presentation and delivery of data mining deliverables- Domain driven data mining evaluation system- Trust, reputation, cost, benefit, risk, privacy, utilityand other issues in data mining- Post-mining, transfer mining, from mined patterns andknowledge to operable business rules.- Knowledge actionability, and integrating technical andbusiness interestingness- Reliability, dependability, workability, actionabilityand usability of data mining- Computational performance and actionability enhancement- Handling inconsistencies between mined and existingdomain knowledge(4) Enterprise applications- Dynamic mining, evolutionary mining, real-time streammining, and domain adaptation- Activity, impact, event, process and workflow mining- Enterprise-oriented, spatio-temporal, multiple sourcemining- Domain specific data mining, etc.Important DatesJuly 17, 2009 Due date for full workshop papersSept. 8, 2009 Notification of paper acceptanceSept. 28, 2009 Camera-ready of accepted papersDec. 6, 2009 Workshop dateSubmissionPaper submissions should be limited to a maximum of 10pages in the IEEE 2-column format, the same as thecamera-ready format (see the IEEE Computer Society PressProceedings Author Guidelines). All papers will be reviewedby the Program Committee on the basis of technical quality,relevance to domain driven data mining, originality,significance and clarity.All papers accepted for the workshop will be included inthe ICDM'09 Workshop Proceedings published by the IEEEComputer Society Press. Selected papers from the workshopwill be invited for consideration of publication in aspecial issue of a SCI-indexed journal to be confirmed.Organizing CommitteeGeneral ChairPhilip S Yu University of Illinois at Chicago, USAWorkshop ChairsLongbing Cao University of Technology, Sydney, AustraliaJean-Francois Boulicaut University of Lyon, FranceShusaku Tsumoto Shimane University, JapanOrganizing ChairYanchang Zhao University of Technology, Sydney, AustraliaWebmasterXuchun Su University of Technology, Sydney, AustraliaContactInquiries can be forwarded to kdd(at)it.uts.edu.au.For more information, please refer to the DDDM2009 website:http://datamining.it.uts.edu.au/dddm09/
Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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