Search for dissertations about: "Data Stream Mining"

Showing result 1 - 5 of 20 swedish dissertations containing the words Data Stream Mining.

  1. 1. Data Stream Mining and Analysis : Clustering Evolving Data

    Author : Christian Nordahl; Håkan Grahn; Veselka Boeva; Marie Netz; Plamen Angelov; Blekinge Tekniska Högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Data Stream Mining; Clustering; Data Streams; Data Mining; Computer Science; Datavetenskap;

    Abstract : Streaming data is becoming more prevalent in our society every day. With the increasing use of technologies such as the Internet of Things (IoT) and 5G networks, the number of possible data sources steadily increases. Therefore, there is a need to develop algorithms that can handle the massive amount of data we now generate. READ MORE

  2. 2. Energy Efficiency in Machine Learning : Approaches to Sustainable Data Stream Mining

    Author : Eva García Martín; Håkan Grahn; Veselka Boeva; Emiliano Casalicchio; Jesse Read; Blekinge Tekniska Högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; machine learning; energy efficiency; data stream mining; green machine learning; edge computing; Computer Science; Datavetenskap;

    Abstract : Energy efficiency in machine learning explores how to build machine learning algorithms and models with low computational and power requirements. Although energy consumption is starting to gain interest in the field of machine learning, still the majority of solutions focus on obtaining the highest predictive accuracy, without a clear focus on sustainability. READ MORE

  3. 3. Data Mining Approaches for Outlier Detection Analysis

    Author : Shahrooz Abghari; Niklas Lavesson; Håkan Grahn; Veselka Boeva; Olga Fink; Blekinge Tekniska Högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; outlier detection; data modelling; machine learning; clustering analysis; data stream mining; Computer Science; Datavetenskap;

    Abstract : Outlier detection is studied and applied in many domains. Outliers arise due to different reasons such as fraudulent activities, structural defects, health problems, and mechanical issues. The detection of outliers is a challenging task that can reveal system faults, fraud, and save people's lives. READ MORE

  4. 4. Extraction and Energy Efficient Processing of Streaming Data

    Author : Eva García-Martín; Niklas Lavesson; Håkan Grahn; Albert Bifet; Blekinge Tekniska Högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; machine learning; green computing; data mining; data stream mining; green machine learning;

    Abstract : The interest in machine learning algorithms is increasing, in parallel with the advancements in hardware and software required to mine large-scale datasets. Machine learning algorithms account for a significant amount of energy consumed in data centers, which impacts the global energy consumption. READ MORE

  5. 5. Big Data Analytics for Fault Detection and its Application in Maintenance

    Author : Liangwei Zhang; Ramin Karim; Janet Lin; Benoît Iung; Luleå tekniska universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Big Data analytics; eMaintenance; fault detection; high-dimensional data; stream data mining; nonlinear data; Drift och underhållsteknik; Operation and Maintenance;

    Abstract : Big Data analytics has attracted intense interest recently for its attempt to extract information, knowledge and wisdom from Big Data. In industry, with the development of sensor technology and Information & Communication Technologies (ICT), reams of high-dimensional, streaming, and nonlinear data are being collected and curated to support decision-making. READ MORE