Conference Information
SIMBig 2018: The Symposium on Information Management and Big Data
http://simbig.org/SIMBig2018/index.htmlSubmission Date: |
2018-05-14 |
Notification Date: |
2018-06-14 |
Conference Date: |
2018-09-03 |
Location: |
Lima, Peru |
Years: |
5 |
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Call For Papers
All submissions will be reviewed by at least three program committee members. The submissions will be judged on originality, relevance, technical quality and presentation. SIMBig is one of the first conferences grouping related areas such as Data Science, Big Data, NLP and Semantic Web, etc, in Latin America. We would like to thank you in advance for your scientific contribution to the 5th SIMBig and look forward to having the opportunity to showcase and disseminate your research. Authors are invited to submit original and innovative papers that break new ground, present insightful results based on your experience in Data Science. SIMBig 2018 has a broad scope, and specific topics of interest include (but are not limited to): -Data Science -Big Data -Data Mining -Natural Language Processing -Semantic Web -Bio NLP, Healthcare Informatics -Text Mining -Information Retrieval -Machine Learning -Ontologies, Knowledge Representation, Linked Open Data -Social Networks, Social Web, and Web Science -Information visualization -OLAP, Data warehousing, Business intelligence -Spatiotemporal Data -Agent-based Systems -Constraints, Satisfiability, and Search
Last updated by Dou Sun in 2018-04-02
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Full Name | Impact Factor | Publisher |
---|---|---|
Interactive Learning Environments | 3.700 | Taylor & Francis |
International Journal of Advanced Computer Science and Applications | 0.700 | Science and Information |
Virtual Reality | 4.400 | Springer |
International Journal of Wireless and Mobile Networking | AR Publication | |
Ecological Informatics | 5.800 | Elsevier |
International Journal of Computer Science Applications & Information Technologies | AR Publication | |
IEEE Software | 3.300 | IEEE |
IEEE Transactions on Geoscience and Remote Sensing | 7.500 | IEEE |
Engineering Optimization | 2.200 | Taylor & Francis |
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