<p>This dissertation contains a set of contributions that deal with search or classification of non-textual information. Each contribution can be considered a solution to a specific problem, in an attempt to map out a common ground. The problems cover a wide range of research fields, including search in music, classifying digitally sampled music, visualization and navigation in search results, and classifying images and Internet sites.</p><p>On classification of digitally sample music, as method for extracting the rhythmic tempo was disclosed. The method proved to work on a large variety of music types with a constant audible rhythm. Furthermore, this rhythmic properties showed to be useful in classifying songs into music groups or genre.</p><p>On search in music, a technique is presented that is based on rhythm and pitch correlation between the notes in a query theme and the notes in a set of songs. The scheme is based on a dynamic programming algorithm which attempts to minimize the error between a query theme and a song. This operation includes finding the best alignment, taking into account skipped notes and additional notes, use of different keys, tempo variations, and variances in pitch and time information.</p><p>On image classification, a system for classifying whole Internet sites based on the image content, was proposed. The system was composed of two parts; an image classifier and a site classifier. The image classifier was based on skin detection, object segmentation, and shape, texture and color feature extraction with a training scheme that used genetic algorithms. The image classification method was able to classify images with an accuracy of 90%. By classifying multi-image Internet web sites this accuracy was drastically increased using the assumption that a site only contains one type of images. This assumption can be defended for most cases.</p><p>On search result visualization and navigation, a system was developed involving the use of a state-of-the-art search engine together with a graphical front end to improve the user experience associated with search in unstructured data. Both structured and unstructured data with the help of entity extraction can be indexed in a modern search engine. Combining this with a multidimensional visualization based on heatmaps with navigation capabilities showed to improve the data value and search experience on current search systems.</p> / Paper III reprinted with kind permission of Elsevier Publishing, sciencedirect.com.
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:ntnu-229 |
| Date | January 2004 |
| Creators | Arentz, Will Archer |
| Publisher | Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, Fakultet for informasjonsteknologi, matematikk og elektroteknikk |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Doctoral thesis, comprehensive summary, text |
| Relation | Doktoravhandlinger ved NTNU, 1503-8181 ; 2004:51 |
Page generated in 0.0021 seconds