Name
Abstract | ||
|---|---|---|
Text mining is an effective means of detecting potentially useful knowledge from large text documents. However conventional text mining technology cannot achieve high accuracy, because it cannot effectively make use of the semantic information of the text. Ontology provides theoretical basis and technical support for semantic information representation and organization. This paper improves the traditional text mining technology which cannot understand the text semantics. The author discusses the text mining methods based on domain ontology, and sets up domain ontology and database at first, then introduces the "concept-concept" correlation matrix and identifies the relationships of conceptions, and puts forward the text mining model based on domain ontology at last. Based on the semantic text mining model, the depth and accuracy of text mining is improved. © 2013 IFIP International Federation for Information Processing. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-36124-1_40 | IFIP Advances in Information and Communication Technology |
Keywords | Field | DocType |
domain ontology,ontology,semantic text mining,text mining | Ontology (information science),Text graph,Ontology-based data integration,Concept mining,Information retrieval,Process ontology,Computer science,Biomedical text mining,Upper ontology,Semantic computing | Conference |
Volume | Issue | ISSN |
392 AICT | PART 1 | null |
Citations | PageRank | References |
0 | 0.34 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lihua Jiang | 1 | 1 | 2.41 |
| Hong-bin Zhang | 2 | 0 | 0.68 |
| Xiaorong Yang | 3 | 1 | 2.08 |
| Nengfu Xie | 4 | 18 | 8.62 |