Search for dissertations about: "data mining"

Showing result 1 - 5 of 294 swedish dissertations containing the words data mining.

  1. 1. Everyday mining : Exploring sequences in event-based data

    Author : Katerina Vrotsou; Matthew Cooper; Anders Ynnerman; Kajsa Ellegård; Andrew S. Harvey; Linköpings universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Event-based data; activity diary data; event-sequences; interactive exploration; sequence identification; visual data mining; Computer science; Datavetenskap;

    Abstract : Event-based data are encountered daily in many disciplines and are used for various purposes. They are collections of ordered sequences of events where each event has a start time and a duration. READ MORE

  2. 2. Data mining of geospatial data: combining visual and automatic methods

    Author : Urška Demšar; Hans Hauska; Peter A. Burrough; KTH; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; geographic information science; geoinformatics; geovisualisation; spatial data mining; visual data mining; usability evaluation; Other information technology; Övrig informationsteknik;

    Abstract : Most of the largest databases currently available have a strong geospatial component and contain potentially useful information which might be of value. The discipline concerned with extracting this information and knowledge is data mining. Knowledge discovery is performed by applying automatic algorithms which recognise patterns in the data. READ MORE

  3. 3. Algorithmically Guided Information Visualization : Explorative Approaches for High Dimensional, Mixed and Categorical Data

    Author : Sara Johansson Fernstad; Mikael Jern; Jimmy Johansson; Jane Shaw; Matthew O. Ward; Linköpings universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Information visualization; data mining; high dimensional data; categorical data; mixed data;

    Abstract : Facilitated by the technological advances of the last decades, increasing amounts of complex data are being collected within fields such as biology, chemistry and social sciences. The major challenge today is not to gather data, but to extract useful information and gain insights from it. READ MORE

  4. 4. Legal Implications of Data Mining : Assessing the European Union’s Data Protection Principles in Light of the United States Government’s National Intelligence Data Mining Practices

    Author : Liane Colonna; Cecilia Magnusson Sjöberg; Antonina Bakardjieva-Engelbrekt; Dan Svantesson; Stockholms universitet; []
    Keywords : SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; data mining; data protection; privacy; Directive 95 46 ec; data transfers; EU law; US law; rättsinformatik; Law and Information Technology;

    Abstract : This dissertation addresses some of the data protection challenges that have arisen from globalization, technological progress, terrorism and seamless cross-border flows of personal data.  The focus of the thesis is to examine ways to protect the personal data of EU citizens, which may be collected by communications service providers such as Google and Facebook, transferred to the US Government and data mined within the context of American national intelligence surveillance programs. READ MORE

  5. 5. Utilizing Diversity and Performance Measures for Ensemble Creation

    Author : Tuve Löfström; Högskolan i Skövde; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; Ensemble Learning; Machine Learning; Diversity; Artificial Neural Networks; Data Mining; Information Fusion; Computer science; Datavetenskap; Teknik; Technology; ensemble learning; machine learning; diversity; artificial neural networks; information fusion; Computer Science; data mining;

    Abstract : An ensemble is a composite model, aggregating multiple base models into one predictive model. An ensemble prediction, consequently, is a function of all included base models. Both theory and a wealth of empirical studies have established that ensembles are generally more accurate than single predictive models. READ MORE