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2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology
Intelligent Extraction of Knowledge Structures from Natural Language Texts
Lyon, France
August 22-August 27
ISBN: 978-0-7695-4513-4
| ASCII Text | x | ||
| Igor P. Kuznetsov, Elena B. Kozerenko, Andrew G. Matskevich, "Intelligent Extraction of Knowledge Structures from Natural Language Texts," Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on, vol. 3, pp. 269-272, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2011. | |||
| BibTex | x | ||
| @article{ 10.1109/WI-IAT.2011.235, author = {Igor P. Kuznetsov and Elena B. Kozerenko and Andrew G. Matskevich}, title = {Intelligent Extraction of Knowledge Structures from Natural Language Texts}, journal ={Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on}, volume = {3}, year = {2011}, isbn = {978-0-7695-4513-4}, pages = {269-272}, doi = {http://doi.ieeecomputersociety.org/10.1109/WI-IAT.2011.235}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on TI - Intelligent Extraction of Knowledge Structures from Natural Language Texts SN - 978-0-7695-4513-4 SP269 EP272 A1 - Igor P. Kuznetsov, A1 - Elena B. Kozerenko, A1 - Andrew G. Matskevich, PY - 2011 KW - semantics KW - natural language KW - linguistic processor KW - knowledge engineering KW - data extraction VL - 3 JA - Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on ER - | |||
A semantic linguistic processor which extracts the objects and their links from natural language texts is considered. It is intended for the areas where the automatic formalization of the flows of texts in natural language is required. Peculiarities of the texts are taken into account by linguistic knowledge of the processor: the system can be tuned to various subject areas. We describe the use of this processor for text formalization in different subject areas, such as criminology (summary of incidents, accusatory conclusions, etc.), mass media (documents about terrorist activities), personnel management (autobiographies, resume). Special features of each problem area are examined: the collections of extracted objects, the means for their identification, their connections, occurring contractions, punctuation and special signs, specific character of language constructions, etc. -- all these special features were taken into account in the linguistic knowledge development.
Index Terms:
semantics, natural language, linguistic processor, knowledge engineering, data extraction
Citation:
Igor P. Kuznetsov, Elena B. Kozerenko, Andrew G. Matskevich, "Intelligent Extraction of Knowledge Structures from Natural Language Texts," wi-iat, vol. 3, pp.269-272, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2011
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