A SURVEY STUDY ON INFORMATION EXTRACTION FROM TEXT
published by Aِl-Baath University
in 2017
in
and research's language is
العربية
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Abstract in English
Information extraction is the task of finding structured information
from unstructured or semi-structured text. It is an important task in
text mining and has been extensively studied in various research
communities including natural language processing, information
retrieval and Web mining. It has a wide range of applications in
domains such as biomedical literature mining and business
intelligence. Two fundamental tasks of information extraction are
named entity recognition and relation extraction. The former refers to
finding names of entities such as people, organizations and
locations. The latter refers to finding the semantic relations between
entities.
References used
Douglas E. Appelt, Jerry R. Hobbs, John Bear, David Israel, and Mabry Tyson. FASTUS: A finite-state processor for information extraction from realworld text. In Proceedings of the 13th International Joint Conference on Artificial Intelligence, 1993
Mary Elaine Califf and Raymond J. Mooney. Relational learning of patternmatch rules for information extraction. In Proceedings of the 16th National Conference on Artificial Intelligence and the 11th Innovative Applications of Artificial Intelligence Conference, pages 328–334, 1999
Tao Cheng, Xifeng Yan, and Kevin Chen-Chuan Chang. Supporting entity search: a large-scale prototype search engine. In Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pages 1144–1146, 2007