DocumentCode :
3317612
Title :
Incremental knowledge acquisition for extracting temporal relations
Author :
Pham, Son Bao ; Hoffmann, Achim
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW, Australia
fYear :
2005
fDate :
30 Oct.-1 Nov. 2005
Firstpage :
354
Lastpage :
359
Abstract :
We present KAFTIE - an incremental knowledge acquisition framework which utilizes expert knowledge to build high quality knowledge base annotators. Using KAFTIE, a knowledge base was built based on a small data set that outperforms machine learning algorithms trained on a much bigger data set for the task of recognizing temporal relations. In particular, this can be incorporated to bootstrap the process of labeling data for domains where annotated data is not available.
Keywords :
knowledge acquisition; learning (artificial intelligence); KAFTIE; incremental knowledge acquisition; knowledge base annotator; machine learning algorithm; temporal relation extraction; Computer science; Data mining; Knowledge acquisition; Labeling; Machine learning; Machine learning algorithms; Text categorization; Text recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2005. IEEE NLP-KE '05. Proceedings of 2005 IEEE International Conference on
Print_ISBN :
0-7803-9361-9
Type :
conf
DOI :
10.1109/NLPKE.2005.1598761
Filename :
1598761
Link To Document :
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