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Text mining is an exciting application field and an area of scientific research that is currently under rapid development. It uses techniques from well-established scientific fields (e.g. data mining, machine learning, information retrieval, natural language processing, case-based reasoning, statistics and knowledge management) in an effort to help people gain insight, understand and interpret large quantities of (usually) semi-structured and unstructured data. Despite the advances made during the last few years, many issues remain unresolved.
Knowledge Mining draws upon many of the key
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Produktbeschreibung
Text mining is an exciting application field and an area of scientific research that is currently under rapid development. It uses techniques from well-established scientific fields (e.g. data mining, machine learning, information retrieval, natural language processing, case-based reasoning, statistics and knowledge management) in an effort to help people gain insight, understand and interpret large quantities of (usually) semi-structured and unstructured data. Despite the advances made during the last few years, many issues remain unresolved.

Knowledge Mining draws upon many of the key concepts of knowledge management, data mining and knowledge discovery, meta-analysis and data visualization. Within the context of scientific research, knowledge mining is principally concerned with the quantitative synthesis and visualization of research results and findings.

The book presents results from the application of knowledge mining techniques in various sector of the academic and indystrial research. The results are increased scientific understanding along with improvements in research quality and value. Knowledge mining products can be used to highlight research opportunities, assist with the presentation of "best" scientific evidence, facilitate research portfolio management, as well as, facilitate policy setting and decision making.


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