Knowledge Mining. Cet article n’est pas disponible.Knowledge Mining

Neuware - 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.…