15th International Conference on Data Science (ICDATA’19)

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Formerly the International Conference on Data Mining, this conference is part of CSCE’19 (2019 World Congress in Computer Science, Computer Engineering, and Applied Computing) with 1000-2000 expected participants. CSCE provides a unique platform for a diverse community of constituents composed of scholars, researchers, developers, educators, and practitioners. It assembles a spectrum of affiliated research conferences, workshops, and symposiums into a coordinated research meeting held in a common place at a common time. This model facilitates communication among researchers in different fields of computer science, computer engineering, and applied computing. The Congress also encourages multi-disciplinary and inter-disciplinary research initiatives; ie, facilitating increased opportunities for cross-fertilization across sub-disciplines.‘
When 29 July 2019 12:25 PM to
01 August 2019 12:25 PM
Where Las Vegas NV USA
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Data Mining/Machine Learning 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)
  • Mining „Big Data“
  • Others

Data Mining Algorithms

  • Artificial neural networks / Deep Learning
  • 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/big data
  • Data and knowledge representation
  • Data warehousing and OLAP integration
  • Integration of prior domain knowledge
  • Metadata and ontologies
  • Agent technolog ies for data mining
  • Legal and social aspects of data mining

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 Data Mining
    • Business / Corporate / Industrial Data Mining
    • Credit Scoring
    • Direct Marketing
    • Database Marketing
    • Engineering Mining
    • Military Data Mining
    • Security Data Mining
    • Social Science Mining
    • Data Mining in Logistics
    • Others

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 into consideration.

Data Mining Software

  • All aspects, modules, frameworks

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
    • Case studies and prototypes
    • 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 optimization
    • 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, …)

Algorithms for Big Data

  • Data and Information Fusion
  • Algorithms (including Scalable methods)
  • Natural Language Processing
  • Signal Processing
  • Simulation and Modeling
  • Data-Intensive Computing
  • Parallel Algorithms
  • Testing Methods
  • Multidimensional Big Data
  • Multilinear Subspace Learning
  • Sampling Methodologies
  • Streaming
  • Others

Big Data Fundamentals

  • Novel Computational Methodologies
  • Algorithms for Enhancing Data Quality
  • Models and Frameworks for Big Data
  • Graph Algorithms and Big Data
  • Computational Science
  • Computational Intelligence
  • Others

Infrastructures for Big Data

  • Cloud Based Infrastructures (applications, storage & computing resources)
  • Grid and Stream Computing for Big Data
  • High Performance Computing, Including Parallel & Distributed Processing
  • Autonomic Computing
  • Cyber-infrastructures and System Architectures
  • Programming Models and Environments to Support Big Data
  • Software and Tools for Big Data
  • Big Data Open Platforms
  • Emerging Architectural Frameworks for Big Data
  • Paradigms and Models for Big Data beyond Hadoop/MapReduce, …
  • Others

Big Data Management and Frameworks

  • Database and Web Applications
  • Federated Database Systems
  • Distributed Database Systems
  • Distributed File Systems
  • Distributed Storage Systems
  • Knowledge Management and Engineering
  • Massively Parallel Processing (MPP) Databases
  • Novel Data Models
  • Data Preservation and Provenance
  • Data Protection Methods
  • Data Integrity and Privacy Standards and Policies
  • Data Science
  • Novel Data Management Methods
  • Crowdsourcing
  • Stream Data Management
  • Scientific Data Management
  • Others

Big Data Search

  • Multimedia and Big Data
  • Social Networks
  • Data Science
  • Web Search and Information Extraction
  • Scalable Search Architectures
  • Cleaning Big Data (noise reduction), Acquisition & Integration
  • Visualization Methods for Search
  • Time Series Analysis
  • Recommendation Systems
  • Graph Based Search and Similar Technologies
  • Others

Privacy in the Era of Big Data

  • Cryptography
  • Threat Detection Using Big Data Analytics
  • Privacy Threats of Big Data
  • Privacy Preserving Big Data Collection
  • Intrusion Detection
  • Socio-economical Aspect of Big Data in the Context of Privacy and Security
  • Others

Applications of Big Data

  • Big Data as a Service
  • Big Data Analytics in e-Government and Society
  • Applications in Science, Engineering, Healthcare, Visualization, Business, Education, Security, Humanities, Bioinformatics, Health Informatics, Medicine, Finance, Law, Transportation, Retailing, Telecommunication, all Search-based applications, …
  • Others

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