Intelligent Extraction of Knowledge Structures from Natural Language Texts

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...

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Published in2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Vol. 3; pp. 269 - 272
Main Authors Kuznetsov, I. P., Kozerenko, E. B., Matskevich, A. G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2011
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ISBN9781457713736
145771373X
DOI10.1109/WI-IAT.2011.235

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Abstract 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.
AbstractList 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.
Author Kozerenko, E. B.
Kuznetsov, I. P.
Matskevich, A. G.
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Snippet 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...
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StartPage 269
SubjectTerms Conferences
data extraction
Intelligent agents
knowledge engineering
linguistic processor
natural language
semantics
Title Intelligent Extraction of Knowledge Structures from Natural Language Texts
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Volume 3
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