Search for dissertations about: "Data Science"

Showing result 6 - 10 of 5260 swedish dissertations containing the words Data Science.

  2. 6. Dynamic Adaptations of Synchronization Granularity in Concurrent Data Structures

    Author : Kjell Winblad; Konstantinos Sagonas; Erez Petrank; Uppsala universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; concurrent data structures; contention adapting; range queries; lock-freedom; adaptivity; linearizability; ordered sets; maps; key-value stores; concurrent priority queues; relaxed concurrent data structures; locks; delegation locking; Computer Science; Datavetenskap;

    Abstract : The multicore revolution means that programmers have many cores at their disposal in everything from phones to large server systems. Concurrent data structures are needed to make good use of all the cores. Designing a concurrent data structure that performs well across many different scenarios is a difficult task. READ MORE

  4. 7. Everyday mining : Exploring sequences in event-based data

    Author : Katerina Vrotsou; Matthew Cooper; Anders Ynnerman; Kajsa Ellegård; Andrew S. Harvey; Linköpings universitet; []
    Keywords : 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

  5. 8. 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 : 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

  6. 9. Computer Science Project Courses : Contrasting Students’ Experiences with Teachers’ Expectations

    Author : Mattias Wiggberg; Mats Daniels; Lecia J. Barker; Tony Clear; Uppsala universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; computer science education; computer science student projects; computer science projects; computer science education research; phenomenography; learning; higher education; communities of practice; capstone projects; constructivism; Computer science; Datavetenskap; Datavetenskap med inriktning mot datavetenskapens didaktik; Computer Science with specialization in Computer Science Education Research;

    Abstract : Including small or large project courses is widely recognized as important in preparing computer science students for a professional career. Typical examples are the capstone courses, which often are seen as the jewel in the crown since this is where students will bring their previous knowledge and skills together to show mastery of their craft. READ MORE

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

    Author : Urška Demšar; Hans Hauska; Peter A. Burrough; KTH; []
    Keywords : 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