Search for dissertations about: "visual data mining"
Showing result 1 - 5 of 24 swedish dissertations containing the words visual data mining.
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1. Everyday mining : Exploring sequences in event-based data
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
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2. Data mining of geospatial data: combining visual and automatic methods
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
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3. Algorithmically Guided Information Visualization : Explorative Approaches for High Dimensional, Mixed and Categorical 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
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4. Mining Speech Sounds : Machine Learning Methods for Automatic Speech Recognition and Analysis
Abstract : This thesis collects studies on machine learning methods applied to speech technology and speech research problems. The six research papers included in this thesis are organised in three main areas. The first group of studies were carried out within the European project Synface. READ MORE
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5. A toolbox for idea generation and evaluation : Machine learning, data-driven, and contest-driven approaches to support idea generation
Abstract : Ideas are sources of creativity and innovation, and there is an increasing demand for innovation. For example, the start-up ecosystem has grown in both number and global spread. As a result, established companies need to monitor more start-ups than before and therefore need to find new ways to identify, screen, and collaborate with start-ups. READ MORE