Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
XSLT and XPATH: A Guide to XML Transformations
XSLT and XPATH: A Guide to XML Transformations
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
Natural Language Engineering
KIM – a semantic platform for information extraction and retrieval
Natural Language Engineering
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
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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.