Conference Information
MIKE 2023: International Conference on Mining Intelligence and Knowledge Exploration
Submission Date:
2023-04-30 Extended
Notification Date:
Conference Date:
Kristiansand, Norway
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Call For Papers
The MIKE 2023 Program Committee invites submissions of original theoretical research, applied research and deployed application papers on all aspects of Data Mining, Learning theory and Knowledge Discovery. Example submission areas include, but are not limited to:

    Evolutionary Computation
    We focus on the following topics, but strictly not limited to:

        Evolutionary Computation
        Design of new and improved evolutionary algorithms
        Design of new search operators
        Diversity control
        Hybrid approaches and memetic algorithms
        Local search methods
        Automatic algorithm configuration and design
        Applications of metaheuristics to combinatorial optimization problems
        Development of tailored evolutionary algorithms for specific applications

    Knowledge Exploration in IoT
    We focus on the following topics, but strictly not limited to:

        Physical: world event processing and understanding: novel data collection, deep learning, real-time decision making, event processing, extracting information from large data sets);
        Machine learning and deep learning on sensor data: deep learning models for multimodal sensing and processing, multi-sensor fusion with deep learning);
        IoT: reliability, adaptability, and dependability;
        Technical assessment of emerging IoT standards;
        New hardware and system design to enable machine learning on sensor data;
        Sensor data related issues (e.g., structure, management, methods, tools, analysis, etc.);
        Anomaly detection;
        Data mining of large scale urban networks and big data;
        Human/social behavior mining in urban environments;
        Environmental modelling based on data mining methods.

    Artificial intelligence
    We focus on the following topics, but strictly not limited to:

        Artificial intelligence and philosophy
        Automated reasoning and inference
        Cognitive aspects of AI
        Common-sense reasoning
        Constraint processing
        Heuristic search
        Intelligent interfaces
        Intelligent robotics
        Knowledge representation
        Multi-agent systems
        Reasoning under uncertainty or imprecision
        Applications of AI

    Machine Learning
    We focus on the following topics, but strictly not limited to:

        Decision tree learning
        Association rule learning
        Artificial neural networks
        Deep learning
        Support vector machines
        Bayesian learning
        Reinforcement learning
        Representation learning
        Similarity and metric learning
        Sparse dictionary learning
        Rule-based machine learning
        Learning classifier systems
        Applications of ML
        Applications of ML to various interdisciplinary domains
        Modelling Material Properties,
        Predicting Material Properties
        Predicting Mechanical Properties
        Thermal Properties of Fluids
        Design Materials
        Optimizing Material properties
        Application of Neural Networks
        Fuzzy Logic
        Fuzzy Systems
        Computational Intelligence

    Data Mining and Information Retrieval
    We focus on the following topics, but strictly not limited to:

        Data and knowledge creation and discovery
        Data and knowledge processing, modelling, mapping,
        Data and knowledge search, interoperability, exchange and integration
        Data visualization
        Databases, indexing and query processing
        Data mining: machine learning and deep learning
        Behaviour analytics
        Business analytics
        Customer analytics
        Financial analytics
        Information retrieval and extraction
        Big data infrastructure and visualization
        Scalable computing and high-performance computing for big data
        Parallel and distributed data mining techniques
        Computational intelligence based theories and methods
        Statistical and mathematical techniques
        Large-scale optimization
        Data characteristics and complexities
        Bioinformatics, computational biology, health and medical analytics

    Medical Image Analysis, Pattern Recognition and Computer Vision
    We focus on the following topics, but strictly not limited to:

        Visual search
        Computer vision theory
        Physics-based vision and shape from-X
        3D computer vision
        Vision for graphics
        Vision for robotics
        Vision for web
        Computational photography, sensing and display
        Document and handwriting analysis
        Image and video analysis
        Segmentation, grouping and shape representation
        Motion and tracking
        Content-based retrieval of image and video
        RGBD sensor and analytics
        Recognition: detection, categorization, indexing
        Face and gesture recognition
        Action recognition
        Statistical learning based applications
        Deep learning based applications

    Speech / Signal Processing
    We focus on the following topics, but strictly not limited to:

        Basics of oral communication: modelling of production and perception processes;
        phonetics and phonology; syntax; cognitive aspects
        Models and tools for language learning: functional organization and developmental models of human language capabilities; acquisition and rehabilitation of spoken language;
        Speech signal analysis
        Speech recognition
        Language identification
        Speaker recognition
        Speech synthesis
        Multimodal human computer interface: speech in combination with gesture, handwriting etc
        Forensic voice comparison
        Forensic analysis of disputed utterances
        Speaker identification by earwitness

    Text Mining and Natural Language Processing
    We focus on the following topics, but strictly not limited to:

        Named entity recognition
        Part-of-speech tagging
        Relationship extraction
        Sentence breaking
        Word segmentation
        Morphological segmentation
        Topic segmentation and recognition
        Automatic summarization
        Coreference resolution
        Machine translation
        Natural language generation
        Natural language understanding
        Question answering
        Sentiment analysis
        Word sense disambiguation

    Intelligent Security Systems
    We focus on the following topics, but strictly not limited to:

        Blockchain in Security
        Device log analysis
        Correlation of events posing security threats
        Deep packet analysis
        Network and system behaviour analysis
        User behaviour modelling and analysis
        Intrusion detection
        Intelligent security systems
        Social media analysis for security

    Smart and Intelligent Systems
    We focus on the following topics, but strictly not limited to:

        Smart Cities
        Smart Transportation
        Intelligent V2V and V2I Communication
        Vehicular Networks
        Data Analytics for Real-Time Systems
        System Assisted Driving/ Recommendation Engine
        Deep Learning for smart systems
Last updated by Dou Sun in 2023-04-18
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