Logo des Repositoriums
 

Sequential pattern mining of multimodal streams in the humanities

dc.contributor.authorHassani, Marwan
dc.contributor.authorBeecks, Christian
dc.contributor.authorTöws, Daniel
dc.contributor.authorSerbina, Tatiana
dc.contributor.authorHaberstroh, Max
dc.contributor.authorNiemietz, Paula
dc.contributor.authorJeschke, Sabina
dc.contributor.authorNeumann, Stella
dc.contributor.authorSeidl, Thomas
dc.contributor.editorSeidl, Thomas
dc.contributor.editorRitter, Norbert
dc.contributor.editorSchöning, Harald
dc.contributor.editorSattler, Kai-Uwe
dc.contributor.editorHärder, Theo
dc.contributor.editorFriedrich, Steffen
dc.contributor.editorWingerath, Wolfram
dc.date.accessioned2017-06-30T11:40:52Z
dc.date.available2017-06-30T11:40:52Z
dc.date.issued2015
dc.description.abstractResearch in the humanities is increasingly attracted by data mining and data management techniques in order to efficiently deal with complex scientific corpora. Particularly, the exploration of hidden patterns within different types of data streams arising from psycholinguistic experiments is of growing interest in the area of translation process research. In order to support psycholinguistic experts in quantitatively discovering the non-self-explanatory behavior of the data, we propose the e-cosmos miner framework for mining, generating and visualizing sequential patterns hidden within multimodal streaming data. The introduced MSS-BE algorithm, based on the PrefixSpan method, searches for sequential patterns within multiple streaming inputs arriving from eye tracking and keystroke logging data recorded during translation tasks. The e-cosmos miner enables psycholinguistic experts to select different sequential patterns as they appear in the translation process, compare the evolving changes of their statistics during the process and track their occurrences within a special simulator.en
dc.identifier.isbn978-3-88579-635-0
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2015)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-241
dc.titleSequential pattern mining of multimodal streams in the humanitiesen
dc.typeText/Conference Paper
gi.citation.endPage686
gi.citation.publisherPlaceBonn
gi.citation.startPage683
gi.conference.date2.-3. März 2015
gi.conference.locationHamburg

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
683.pdf
Größe:
234.03 KB
Format:
Adobe Portable Document Format