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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Rattasit Sukhahuta | en_US |
dc.contributor.author | Chadchai Sukanun | en_US |
dc.date.accessioned | 2018-09-04T04:19:39Z | - |
dc.date.available | 2018-09-04T04:19:39Z | - |
dc.date.issued | 2011-07-21 | en_US |
dc.identifier.other | 2-s2.0-79960397154 | en_US |
dc.identifier.other | 10.1109/JCSSE.2011.5930104 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960397154&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/49878 | - |
dc.description.abstract | In 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.subject | Computer Science | en_US |
dc.title | Event recognition from information-linkage based using phrase tree traversal | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | Proceedings of the 2011 8th International Joint Conference on Computer Science and Software Engineering, JCSSE 2011 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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