Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/49878
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRattasit Sukhahutaen_US
dc.contributor.authorChadchai Sukanunen_US
dc.date.accessioned2018-09-04T04:19:39Z-
dc.date.available2018-09-04T04:19:39Z-
dc.date.issued2011-07-21en_US
dc.identifier.other2-s2.0-79960397154en_US
dc.identifier.other10.1109/JCSSE.2011.5930104en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960397154&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/49878-
dc.description.abstractIn this paper we present an approach to extracting significant events from digital documents. OpenNLP syntactical parser for English is used for generating parse trees from the sentences, followed by the extraction of events from the parse trees using tree traversal algorithms. The extraction system is developed and tested on 50 sentences from terrorism documents of The Federation of American Scientists (FAS). The results showed that with this technique we can achieve high recall and precision yielding accuracy of 89.68 recall and 78.44 precision with an overall performance of 83.66 in term of F-measure. © 2011 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.titleEvent recognition from information-linkage based using phrase tree traversalen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleProceedings of the 2011 8th International Joint Conference on Computer Science and Software Engineering, JCSSE 2011en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.