March 1 - 2, 2018

Call for Papers

The concept of big data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. But even in the 1950s, decades before anyone uttered the term " big data," businesses were using basic analytics (essentially numbers in a spreadsheet that were manually examined) to uncover insights and trends. The new benefits that big data analytics brings to the table, however, are speed and efficiency. Whereas a few years ago a business would have gathered information, run analytics and unearthed information that could be used for future decisions, today that business can identify insights for immediate decisions. The ability to work faster - and stay agile - gives organizations a competitive edge they didn't have before.

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers. A central goal of artificial intelligence has long been to construct a complete intelligent agent that can perceive its environment, generate plans, execute those plans, and communicate with other agents. The pursuit of this dream naturally led many researchers to focus on the component tasks of perception, planning, control, and natural language, or on generic issues that cut across these tasks, such as representation and search. Over the years, the AI field has gradually fragmented into many distinct communities, each concerned with a different facet of intelligent behavior.

Topics in ICBAIT'18 include, but are not limited to:

  • Methodology and best practices to implement big data driven KM
  • Business information processing and business models in the Internet of Things
  • Reasoning algorithms for the knowledge systems in the Internet of Things
  • Governance, Ethics and Trust in IoT and Big Data in KM
  • Big Data and Cloud Computing - Big Data Computing for Knowledge Management
  • Semantic web data management
  • Large-scale network data analysis
  • Large data stream processing on cloud
  • Large incremental datasets on cloud
  • Security and privacy in Big Data
  • Volume, velocity and variety of Big Data on cloud
  • Big data and innovation
  • Use Cases and Applications in Knowledge and Big Data analytics
  • Data mining theory, methods, and applications
  • Data warehousing and business intelligence
  • Big Data theory, analytics, applications, processing tools and visualization
  • Social Networks Analysis
  • Big data machine learning-as-a-Service
  • Turning big data health informatics into WWW services
  • Big data deep learning-as-a-Service
  • Big data infrastructure-as-a-Service
  • Infrastructures for big data analytics
  • Big data text analytics
  • Social media analytics
  • Business forecasting
  • Intelligent information systems
  • Predictive analytics

Submission of full papers presenting novel ideas of knowledge management, big data, cloud computing, innovations and IoT are welcomed. Papers should contain original contributions not published or submitted elsewhere, and references to related state-of-the-art work

Instructions for Authors

Papers reporting original and unpublished research results pertaining to the above topics are solicited . Full paper and all submissions deadline is 9th February, 2018. These papers will follow an academic review process. All submitted papers will undergo a thorough review process; each paper will be refereed by at least three experts in the field, based on relevance, originality, significance, quality and clarity.

Submitting Papers: The authors are requested to submit full papers according to the IEEE format attached (click here). The authors are requested to submit their original research papers in .doc file format, by e-mail to

Publication: Accepted papers will be included in the ICBAIT-2018 Proceedings. At least one of the authors will be required to register and attend the conference to present the paper in order to include the paper in the conference proceedings. All accepted papers will be published in the reputed journal indexed in Scopus and recognized by the UGC.

Important Dates:

  • Date of Conference : 1st and 2nd March, 2018
  • Last Date for Submission of paper : 9th February, 2018 - 17th February, 2018
  • Acceptance notification : 16th February, 2018 - 21st February, 2018
  • Last date for Registration : 21st February, 2018 - 28th February, 2018


To motivate the students about the growing developments in Machine learning and to study about the various algorithms and the complexity involved in the algorithms a Tutorial session is arranged in the forenoon session on 2nd March 2018. The Tutorial will give an in depth knowledge about methodology developed to build a machine to learn and do things according to the situation.

Poster Presentation:

Contributed Papers, if selected for posters, will be intimated separately.
Best Award for Poster Presentation
For any queries contact Co-Convenor

  • Six A4 sheet content allowed in 2x3 ft paper/chart format

Registration Fees:

  • Students: 1000/- (ME, MTech, M.Phil, M.Sc, MCA)
  • Research Scholars : 1500/-
  • Faculty members : 2000/-
  • Industry participants : 2500/-
  • Foreign participants : USD 400
  • Registration for Tutorial : 1000/-
  • Conference & Tutorial : Conference Fee + Tutorial Fee

Mode of Payment:

Account Name Department of Computer Science
Account Number 37482180024
Name of Bank State Bank of India
IFSC Code SBIN0002235
Branch Madurai Kamaraj University


  • Blind Review by experts
  • Accepted papers in Scopus Indexed Journals and UGC approved Journals.
  • Conference proceeding in e-book with ISBN
  • Presentation and Publication certificates
  • Presentation through SKYPE (on genuine reasons)
  • Best paper award
  • Poster Presentation


  • Co-Convener, ICBAIT 2018,
  • Department of Computer Science,
  • Madurai Kamaraj University,
  • Madurai - 625 021,
  • Tamil Nadu, India.
  • Phone : +91 75399-74848
  • Mail Id :