The Program Committee of the Third International Conference on Intelligent Information Technologies (ICIIT - 2018) invites the submission of technical papers for the main track of the conference. Submissions are invited on significant, original, and previously unpublished research on all aspects of Data Science & Analytics for publication in the conference proceedings. Papers may address any area of Data Science & Analytics, including those identified in the conference topics. All paper submissions will be peer-reviewed (double-blind review process) by an international panel of experts and will receive mindful and rigorous reviews. The review process will retain the anonymity of authors and reviewers. After review, authors of borderline papers may submit a rebuttal (the meta-review will clearly state where this is appropriate).

CONFERENCE TRACKS

    Data Science Foundations
        Foundational theories and models of data science
        Foundational algorithms and methods for big data
        Feature selection, transformation and construction
        Data classification and taxonomy
        Data metrics and metrology
        Machine learning and deep learning
        Data analytics
        Data preservation and provenance
        Fault tolerance, reliability and availability
        Security, privacy and trust in Data

    Data Processing Technologies
        Data sensing, fusion and mining
        Dimensionality reduction, processing and proactive service layers
        Data capturing, and scheduling techniques
        Stream data processing and integration
        Parallel and distributed data storage and processing infrastructure
        MapReduce, Hadoop, Spark, scalable computing and storage platforms
        Replication, archiving, preservation strategies
        Remote data access

    Data Management and Analytics
        Data warehouses and large-scale databases
        Massively Parallel Processing (MPP) Databases
        Memory, disk and cloud-based storage and analytics
        High performance computing and processing
        Information visualization and visual data analytics
        Information and knowledge retrieval and semantic search
        Human-machine interaction and interfaces
        Stream Data Management and Analytics
        Multimedia Data Analytics

    Data Science & its Applications
        Text analytics and NLP
        Data-intensive applications and their challenges
        Social mining analytics and applications
        Human-in-the-loop systems
        Crowdsourcing and collective intelligence applications
        Robotics
        Data science applications in healthcare, education, social science, business, transportation, energy, telecommunications, science, and humanities