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DMIN 2009 : The International Conference on Data MiningConference Series : International Conference on Data Mining | |||||||||||||||
Link: http://www.world-academy-of-science.org/worldcomp09/ws/conferences/dmin09 | |||||||||||||||
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Call For Papers | |||||||||||||||
You are invited to submit a full paper for consideration. All accepted papers will be published in the conference proceedings/book.
Topics of interest include, but are not limited to, the following: Data Mining Tasks - Regression/Classification - Time series forecasting - Segmentation/Clustering/Association - Deviation and outlier detection - Explorative and visual data mining - Web mining - Mining text and semi-structured data - Temporal and spatial data mining - Multimedia mining (audio/video) - Others Data Mining Algorithms - Artificial neural networks - Fuzzy logic and rough sets - Decision trees/rule learners - Support vector machines - Evolutionary computation/meta heuristics - Statistical methods - Collaborative filtering - Case based reasoning - Link and sequence analysis - Ensembles/committee approaches - Others Data Mining Integration - Mining large scale data - Distributed and grid based data mining - Data and knowledge representation - Data warehousing and OLAP integration - Integration of prior/domain knowledge - Metadata and ontologies - Agent technologies for data mining - Legal and social aspects of data mining - Others Data Mining Process - Data cleaning and preparation - Feature selection and transformation - Attribute discretisation and encoding - Sampling and rebalancing - Missing value imputation - Model selection/assessment and comparison - Induction principles - Model interpretation - Others Data Mining Applications - Bioinformatics/Medicine - Business/Industrial - Engineering - Military/Security - Social science - Others Data Mining Software We particularly encourage submissions of industrial applications and case studies from practitioners. These will not be evaluated using solely theoretical research criteria, but will take general interest and presentation stringer into consideration. Alternative and additional examples of possible topics include: Data Mining for Business Intelligence; Emerging technologies in data mining; Computational performance issues in data mining; Data mining in usability; Advanced prediction modelling using data mining; Data mining and national security; Data mining tools; Data analysis; Data preparation techniques (selection, transformation, and preprocessing); Information extraction methodologies; Clustering algorithms used in data mining; Genetic algorithms and categorization techniques used in data mining; Data and information integration; Microarray design and analysis; Privacy-preserving data mining; Active data mining; Statistical methods used in data mining; Multidimensional data; Automatic data cleaning; Data visualization; Theory and practice (knowledge representation and discovery); Knowledge Discovery in Databases (KDD); Uncertainty management; Data reduction methods; Data engineering; Content mining; Indexing schemes; Information retrieval; Metadata use and management; Multidimensional query languages and query; Multimedia information systems; Search engine query processing; Pattern mining; Applications (examples: data mining in education, marketing, finance and financial services, business applications, medicine, bioinformatics, biological sciences, science and technology, industry and government, ...). |
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