| dc.date.accessioned |
2015-12-18T14:40:24Z |
und |
| dc.date.accessioned |
2017-10-24T12:24:05Z |
|
| dc.date.available |
2015-12-18T14:40:24Z |
und |
| dc.date.available |
2017-10-24T12:24:05Z |
|
| dc.date.issued |
2015-12-18T14:40:24Z |
|
| dc.identifier.uri |
http://radr.hulib.helsinki.fi/handle/10138.1/5244 |
und |
| dc.identifier.uri |
http://hdl.handle.net/10138.1/5244 |
|
| dc.title |
Designing interfaces for exploratory content based image retrieval systems |
en |
| ethesis.department.URI |
http://data.hulib.helsinki.fi/id/225405e8-3362-4197-a7fd-6e7b79e52d14 |
|
| ethesis.department |
Institutionen för datavetenskap |
sv |
| ethesis.department |
Department of Computer Science |
en |
| ethesis.department |
Tietojenkäsittelytieteen laitos |
fi |
| ethesis.faculty |
Matematisk-naturvetenskapliga fakulteten |
sv |
| ethesis.faculty |
Matemaattis-luonnontieteellinen tiedekunta |
fi |
| ethesis.faculty |
Faculty of Science |
en |
| ethesis.faculty.URI |
http://data.hulib.helsinki.fi/id/8d59209f-6614-4edd-9744-1ebdaf1d13ca |
|
| ethesis.university.URI |
http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97 |
|
| ethesis.university |
Helsingfors universitet |
sv |
| ethesis.university |
University of Helsinki |
en |
| ethesis.university |
Helsingin yliopisto |
fi |
| dct.creator |
Hore, Sayantan |
|
| dct.issued |
2015 |
|
| dct.language.ISO639-2 |
eng |
|
| dct.abstract |
Content Based Image Retrieval or CBIR systems have become the state of the art image retrieval technique over the past few years. They showed commendable retrieval performance over traditional annotation based retrieval. CBIR systems use relevance feedback as input query. CBIR systems developed so far did not put much effort to come up with suitable user interfaces for accepting relevance feedback efficiently i.e. by putting less cognitive load to the user and providing a higher amount of exploration in a limited amount of time. In this study we propose a new interface 'FutureView' which allows peeking into the future providing access to more images in less time than traditional interfaces. This idea helps the user to choose more appropriate images without getting diverted. We used Gaussian process upper confidence bound algorithm for recommending images. We successfully compared this algorithm with Random and Exploitation algorithms with positive results. |
en |
| dct.language |
en |
|
| ethesis.language.URI |
http://data.hulib.helsinki.fi/id/languages/eng |
|
| ethesis.language |
English |
en |
| ethesis.language |
englanti |
fi |
| ethesis.language |
engelska |
sv |
| ethesis.thesistype |
pro gradu-avhandlingar |
sv |
| ethesis.thesistype |
pro gradu -tutkielmat |
fi |
| ethesis.thesistype |
master's thesis |
en |
| ethesis.thesistype.URI |
http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis |
|
| ethesis.degreeprogram |
Networking and Service |
en |
| dct.identifier.urn |
URN:NBN:fi-fe2017112251290 |
|
| dc.type.dcmitype |
Text |
|
