Show simple item record

dc.contributor.authorIshikawa, Shota
dc.contributor.authorArakawa, Yutaka
dc.contributor.authorTagashira, Shigeaki
dc.contributor.authorFukuda, Akira
dc.contributor.editorMühl, Gero
dc.contributor.editorRichling, Jan
dc.contributor.editorHerkersdorf, Andreas
dc.date.accessioned2018-11-14T09:29:10Z
dc.date.available2018-11-14T09:29:10Z
dc.date.issued2012
dc.identifier.isbn978-3-88579-294-9
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/18096
dc.description.abstractAs microblog services become increasingly popular, spatial-temporal text data has increased explosively. Many studies have proposed methods to spatially and temporally analyze an event, indicated by the text data. These studies have aimed a extracting the period and the location in which a specified topic frequently occurs. In this paper, we focus on a system that detects hot topic in a local area and during a particular period. There can be a variation in the words used even though the posts are essentially about the same hot topic. We propose a classification method that mitigates the variation of posted words related to the same topic.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofARCS 2012 Workshops
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-200
dc.titleHot topic detection in local areas using twitter and wikipediaen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages165-174
mci.conference.sessiontitleRegular Research Papers
mci.conference.locationMünchen
mci.conference.date28. Februar-2. März 2012


Files in this item

Thumbnail

Show simple item record