| dc.date.accessioned |
2016-08-17T10:01:23Z |
und |
| dc.date.accessioned |
2017-10-24T12:24:14Z |
|
| dc.date.available |
2016-08-17T10:01:23Z |
und |
| dc.date.available |
2017-10-24T12:24:14Z |
|
| dc.date.issued |
2016-08-17T10:01:23Z |
|
| dc.identifier.uri |
http://radr.hulib.helsinki.fi/handle/10138.1/5724 |
und |
| dc.identifier.uri |
http://hdl.handle.net/10138.1/5724 |
|
| dc.title |
Event detection in interaction network |
en |
| ethesis.discipline |
Computer science |
en |
| ethesis.discipline |
Tietojenkäsittelytiede |
fi |
| ethesis.discipline |
Datavetenskap |
sv |
| ethesis.discipline.URI |
http://data.hulib.helsinki.fi/id/1dcabbeb-f422-4eec-aaff-bb11d7501348 |
|
| 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 |
Xiao, Han |
|
| dct.issued |
2016 |
|
| dct.language.ISO639-2 |
eng |
|
| dct.abstract |
We study the problem of detecting top-k events from digital interaction records (e.g, emails, tweets). We first introduce interaction meta-graph, which connects associated interactions. Then, we define an event to be a subset of interactions that (i) are topically and temporally close and (ii) correspond to a tree capturing information flow. Finding the best event leads to one variant of prize-collecting Steiner-tree problem, for which three methods are proposed. Finding the top-k events maps to maximum k-coverage problem. Evaluation on real datasets shows our methods detect meaningful events. |
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 |
|
| dct.identifier.urn |
URN:NBN:fi-fe2017112251192 |
|
| dc.type.dcmitype |
Text |
|
