Event recognition from information-linkage based using phrase tree traversal
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...
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2018
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th-cmuir.6653943832-498782018-09-04T04:19:39Z Event recognition from information-linkage based using phrase tree traversal Rattasit Sukhahuta Chadchai Sukanun Computer Science 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. 2018-09-04T04:19:39Z 2018-09-04T04:19:39Z 2011-07-21 Conference Proceeding 2-s2.0-79960397154 10.1109/JCSSE.2011.5930104 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960397154&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/49878 |
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Thailand |
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Computer Science |
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Computer Science Rattasit Sukhahuta Chadchai Sukanun Event recognition from information-linkage based using phrase tree traversal |
| description |
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. |
| format |
Conference Proceeding |
| author |
Rattasit Sukhahuta Chadchai Sukanun |
| author_facet |
Rattasit Sukhahuta Chadchai Sukanun |
| author_sort |
Rattasit Sukhahuta |
| title |
Event recognition from information-linkage based using phrase tree traversal |
| title_short |
Event recognition from information-linkage based using phrase tree traversal |
| title_full |
Event recognition from information-linkage based using phrase tree traversal |
| title_fullStr |
Event recognition from information-linkage based using phrase tree traversal |
| title_full_unstemmed |
Event recognition from information-linkage based using phrase tree traversal |
| title_sort |
event recognition from information-linkage based using phrase tree traversal |
| publishDate |
2018 |
| url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960397154&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/49878 |
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1681423489270022144 |