Semantic XML tagging of domain-specific text archives: a knowledge discovery approach
نویسنده
چکیده
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منابع مشابه
Semi-automated Xml Tagging of Public Text Archives: a Case Study
Public archives contain large and continuously growing volumes of electronically available text documents. In many countries, public authorities are required by law to publish certain data to satisfy the information needs of the general public. In contrast to plain text documents, semantically tagged XML documents along with appropriate query languages largely facilitate searching and browsing ...
متن کاملThe DIAsDEM Framework for Converting Domain-Specific Texts into XML Documents with Data Mining Techniques
Modern organizations are accumulating huge volumes of textual documents. To turn archives into valuable knowledge sources, textual content must become explicit and queryable. Semantic tagging with markup languages such as XML satisfies both requirements. We thus introduce the DIAsDEM framework for extracting semantics from structural text units (e.g., sentences), assigning XML tags to them and ...
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Ontologies are commonly used to represent formal semantics in a computer system, usually capturing them in the form of concepts, relationships and axioms. Axioms convey asserted knowledge and support inferring new knowledge through logical reasoning. For complex systems, the process of creating ontologies manually can be tedious and error-prone. Many automated methods of knowledge discovery are...
متن کاملSemantic Tagging of Domain-Specific Text Documents with DIAsDEM
Large volumes of electronically available information are stored in textual form. The extraction of semantics from these documents and the characterization of their contents into a databaselike schema is a necessary prerequisite for efficient search and for the fusion of documents semantically belonging together, be they documents about the same company, police reports or legal attests related ...
متن کاملEmploying Text Mining for Semantic Tagging in DIAsDEM
Both public and private organizations have been accumulating large volumes of electronically available text documents for the past years. However, to turn text archives into profitable sources of knowledge, they should be transformed into an integrated and efficiently queryable information system. To attain this objective, the project DIAsDEM employs data mining techniques to derive a semantic ...
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