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Knowledge Mining - Proceedings of the NEMIS 2004 Final Conference (Hardcover, 2005 ed.)
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Knowledge Mining - Proceedings of the NEMIS 2004 Final Conference (Hardcover, 2005 ed.)
Series: Studies in Fuzziness and Soft Computing, 185
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Text mining is an exciting application ?eld and an area of
scienti?c - search that is currently under rapid development. It
uses techniques from well-established scienti?c ?elds (e. g. data
mining, machine learning, infor- tion retrieval, natural language
processing, case-based reasoning, statistics and knowledge
management) in an e?ort to help people gain insight, und- stand and
interpret large quantities of (usually) semi-structured and unstr-
tured data. Despite the advances made during the last few years,
many issues remain unresolved. Proper co-ordination activities,
dissemination of current trends and standardisation of the
procedures have been identi?ed, as key needs. There are many
questions still unanswered, especially to the potential users; what
is the scope of Text Mining, who uses it and for what purpose, what
constitutes the leading trends in the ?eld of Text Mining -
especially in relation to IT - and whether there still remain areas
to be covered. 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
scienti?c research, knowledge mining is principally concerned with
the quantitative synthesis and visualization of - search results
and ?ndings. The results of knowledge mining are increased
scienti?c understanding along with improvements in research quality
and value. Knowledge mining products can be used to highlight
research opportunities, assist with the p- sentation of "best"
scienti?c evidence, facilitate research portfolio mana- ment, as
well as, facilitate policy setting and decision making.
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