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dc.contributor.authorGrünewald, Franka
dc.contributor.authorSiebert, Maria
dc.contributor.authorSchulze, Alexander
dc.contributor.authorMeine, Christoph
dc.contributor.editorDesel, Jörg
dc.contributor.editorHaake, Jörg M.
dc.contributor.editorSpannagel, Christian
dc.date.accessioned2017-09-29T21:21:23Z
dc.date.available2017-09-29T21:21:23Z
dc.date.issued2012
dc.identifier.isbn978-3-88579-601-5
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/4789
dc.description.abstractParsing user access log files for retrieving additional information is a well known approach to obtaining additional knowledge of a web site. Most research interests focus on identifying users and tracking user behaviour. In contrast, this paper concentrates on the statistical evaluation of all available log data. Therefore, special items of a web page are detected, categorized and the access data of these items is analysed. This paper shows the related process using the example of an e-learning web portal. It starts with preparing the log data and analysing it manually. Afterwards the data is categorized according to the findings of the analysis and the results proven by manually selected test data. Based on categories, it is possible to recommend tele-teaching objects with similar access data and classify them automatically to these categories.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDeLFI 2012: Die 10. e-Learning Fachtagung Informatik der Gesellschaft für Informatik e.V.
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-207
dc.titleAutomatic categorization of lecture videos: using statistical log file analysis to enhance tele-teaching metadataen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages51-62
mci.conference.sessiontitleForschungsbeiträge
mci.conference.locationHagen
mci.conference.date24.-26. September 2012


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