Partition document clustering using ontology approach

• Published in: 2013 International Conference on Computer Communication and Informatics pp. 1 - 5
• Main Authors: Punitha, S. C., Jayasree, R., Punithavalli, M.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.01.2013
• Subjects: Algorithm design and analysis; Classification; Clustering; Clustering algorithms; Computers; Conferences; Data mining; Data warehousing; Educational institutions; Knowledge management; Ontologies; Partitioning algorithms; Repositories; Texts
• ISBN: 1467329061; 9781467329064
• DOI: 10.1109/ICCCI.2013.6466246

Data mining is the extraction of hidden predictive information from large databases and it is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. In data mining there are two activities such as Classification and clustering [5]. Text clustering typically involves clustering in a high dimensional space, which appears difficult with regard to virtually all practical settings. The creation and deployment of knowledge repositories for managing, sharing, and reusing tacit knowledge within an organization has emerged as a prevalent approach in current knowledge management practices.