ICDATA 2019: International Conference on Data Science
- Call for paper, ranking, acceptance rate,
submission deadline, notification date, conference location, submission guidelines, and other important details
This article provides the call for paper, ranking, acceptance rate,
submission deadline, notification date, conference location, submission guidelines, and other important details of ICDATA 2019: International Conference on Data Science all at one place.
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Conference Location
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Las Vegas, Nevada, USA
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Conference Date
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2019-07-29
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Notification Date
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2019-04-12
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Submission Deadline
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2019-03-26
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Conference Website and Submission Link
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https://icdatascience.org/
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Conference Ranking
International Conference on Data Science ranking based on CCF, Core, and Qualis is shown below:
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CCF Ranking
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Core Ranking
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Qualis Ranking
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Click here to check the ranking of any conference.
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About CCF Ranking: The Chinese Computing Federation (CCF) Ranking provides a ranking of peer-reviewed journals and conferences in the field of computer science.
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About Core Ranking: The CORE Conference Ranking is a measure to assess the major conference in the computing field. This ranking is governed by the CORE Executive Committee. To know more about Core ranking, visit Core ranking portal.
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About Qualis Ranking: This conference ranking is published by the Brazilian ministry of education. It uses the h-index as a performance metric to rank conferences. Conferences are classified into performance groups that range from A1 (to the best), A2, B1, B2,..., B5 (to the wost). To know more about qualis ranking, visit here
Conference Acceptance Rate
Below is the acceptance rate of International Conference on Data Science conference for the last few years:
| Year |
Submitted Papers |
Accepted Papers |
Accepted Percentage/Acceptance Rate |
We are working hard to collect and update the acceptance rate details of the conferences for recent years. However, you can consider the above (if available) acceptance rates to predict the average chances of acceptance of your research paper at this conference.
Conference Call for paper
INVITATION:You are invited to submit a paper for consideration. All accepted papers will be published in printed conference books/proceedings (each with a unique international ISBN number) and will also be made available online. The proceedings will be indexed in science citation databases that track citation frequency/data. In addition, like prior years, extended versions of selected papers (about 40%) will appear in journals and edited research books; publishers include, Springer, Elsevier, BMC, and others).The Congress is composed of a number of tracks (joint-conferences, tutorials, sessions, workshops, poster and panel discussions); all will be held simultaneously, same location and dates: July 30-August 2, 2018. The complete list of CSCE joint conferences can be found here. ICDATA is part of the Congress.SCOPE: Submitted papers should be related to Data Science, Data Mining, Machine Learning and similar topics.Topics of interest include, but are not limited to, the following: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“
OthersData 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
OthersData 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 miningData 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
OthersData 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
OthersWe 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, frameworksAlternative 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
OthersBig 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
OthersInfrastructures 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, …
OthersBig 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
OthersBig 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
OthersPrivacy 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
OthersApplications 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
Submission Deadline
ICDATA 2019: International Conference on Data Science submission deadline is 2019-03-26.
Note: It is generally recommended to submit your conference paper
on or before the submission deadline. Generally, conferences do not
encourage to submit the research paper after the deadline is over.
In rare scenarios, conferences extend their deadline. Decision about the
extension of the deadline is generally updated on the official conference webpage.
Notification date
Notification date of ICDATA 2019: International Conference on Data Science is 2019-04-12.
Note: This is the date on which conference announces the result about acceptance or rejection of submitted papers. If your research paper is accepted, the conference will request you to submit the camera ready version of your research paper by the due date. Due date to submit the camera ready version of the paper is generally posted on the official web page of the conferences or notified to you via. email.
Conference Date
ICDATA 2019: International Conference on Data Science will start on 2019-07-29.
Note: This is the date on which the conference starts.
Conference Location
ICDATA 2019: International Conference on Data Science will be organized at Las Vegas, Nevada, USA. This is the place where the conference is organized and the research paper is to be presented.
