Analysis and improvement of minimally supervised machine learning for relation extraction
作者： Hans Uszkoreit , Feiyu Xu , Hong Li
DOI: 10.1007/978-3-642-12550-8_2
关键词:
摘要: … supervised machine learning method for relation extrac… learning graph which is a subgraph of the bipartite graph representing all connections between linguistic patterns and relation …
springer.com
sci-hub.st 参考文章(17)
Rosie Jones, Learning to Extract Entities from Labeled and Unlabeled Text ,(2005)
Sergey Brin, Extracting Patterns and Relations from the World Wide Web Lecture Notes in Computer Science. pp. 172- 183 ,(1999) , 10.1007/10704656_11
Sebastian Blohm, Philipp Cimiano, Using the web to reduce data sparseness in pattern-based information extraction european conference on principles of data mining and knowledge discovery. pp. 18- 29 ,(2007) , 10.1007/978-3-540-74976-9_6
Luis Gravano, Eugene Agichtein, Extracting Relations from Large Plain-Text Collections Department of Computer Science, Columbia University. ,(1999) , 10.7916/D8NG4ZHK
Ralph Grishman, Roman Yangarber, Scenario customization for information extraction New York University. ,(2000)
Avrim Blum, Tom Mitchell, None, Combining labeled and unlabeled data with co-training conference on learning theory. pp. 92- 100 ,(1998) , 10.1145/279943.279962
Marti A. Hearst, Automatic acquisition of hyponyms from large text corpora Proceedings of the 14th conference on Computational linguistics -. pp. 539- 545 ,(1992) , 10.3115/992133.992154
David Yarowsky, Unsupervised word sense disambiguation rivaling supervised methods Proceedings of the 33rd annual meeting on Association for Computational Linguistics -. pp. 189- 196 ,(1995) , 10.3115/981658.981684
Eugene Agichtein, Luis Gravano, Snowball: extracting relations from large plain-text collections acm international conference on digital libraries. pp. 85- 94 ,(2000) , 10.1145/336597.336644
Hans Uszkoreit, Feiyu Xu, Hong Li, A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity meeting of the association for computational linguistics. pp. 584- 591 ,(2007)