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dc.contributor.authorBouamrane, Matt-Mouley
dc.contributor.authorLuz, Saturnino
dc.contributor.authorMasoodian, Masood
dc.coverage.spatialConference held at Beijing, Chinaen_NZ
dc.date.accessioned2008-12-16T22:04:58Z
dc.date.available2008-12-16T22:04:58Z
dc.date.issued2006
dc.identifier.citationBouamrane, M. – M., Luz, S. & Masoodian, M. (2006) History based visual mining of semi-structured audio and text. In Proceedings of the 12th International Multi-media modelling conference, MMM2006, Beijing, China, Jan, 2006(pp.360-363). Washington, DC, USA: IEEE Computer Society.en_US
dc.identifier.urihttps://hdl.handle.net/10289/1700
dc.description.abstractAccessing specific or salient parts of multimedia recordings remains a challenge as there is no obvious way of structuring and representing a mix of space-based and time-based media. A number of approaches have been proposed which usually involve translating the continuous component of the multimedia recording into a space-based representation, such as text from audio through automatic speech recognition and images from video (keyframes). In this paper, we present a novel technique which defines retrieval units in terms of a log of actions performed on space-based artefacts, and exploits timing properties and extended concurrency to construct a visual presentation of text and speech data. This technique can be easily adapted to any mix of space-based artefacts and continuous media.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherIEEE Computer Societyen_US
dc.relation.urihttp://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1651349en_US
dc.rightsThis article has been published in Proceedings of the 12th International Multi-media modelling conference, MMM2006, Beijing, China, Jan, 2006. ©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_US
dc.subjectcomputer scienceen_US
dc.subjectvisual data miningen_US
dc.titleHistory-based visual mining of semi-structured audio and texten_US
dc.typeConference Contributionen_US
dc.identifier.doi10.1109/MMMC.2006.1651349en_US
dc.relation.isPartOfThe 12th International Multi-Media Modelling Conferenceen_NZ
pubs.begin-page360en_NZ
pubs.elements-id16200
pubs.end-page363en_NZ
pubs.finish-date2006-01-06en_NZ
pubs.place-of-publicationNew Jersey, USAen_NZ
pubs.start-date2006-01-04en_NZ
pubs.volumeProceedings of the 12th International Multi-Media Modelling Conferenceen_NZ


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