{"title":"自然语言文本知识结构的智能提取","authors":"I. Kuznetsov, E. Kozerenko, A. Matskevich","doi":"10.1109/WI-IAT.2011.235","DOIUrl":null,"url":null,"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.","PeriodicalId":128421,"journal":{"name":"2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":" 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Intelligent Extraction of Knowledge Structures from Natural Language Texts\",\"authors\":\"I. Kuznetsov, E. Kozerenko, A. Matskevich\",\"doi\":\"10.1109/WI-IAT.2011.235\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":128421,\"journal\":{\"name\":\"2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology\",\"volume\":\" 5\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WI-IAT.2011.235\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI-IAT.2011.235","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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 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.