Name
Abstract | ||
|---|---|---|
For the past few years, automatic Ontology construction and expansion is one of the most important research subjects in the field of knowledge engineering. Compared with the traditional Term Frequency method, we propose a semantics-based method to extract concepts from a large corpus of text documents and expand the concepts of the known Ontology based on the semantic relations between two terms. The proposed method explores how to identify the candidate concepts, and how to give suggestions to knowledge engineers on where the concepts should be inserted in a given Ontology. The effectiveness of the proposed approach is demonstrated by experiments on a Traditional Chinese Medicine text corpus. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1363686.1364057 | SAC |
Keywords | Field | DocType |
semantics-based conceptual expansion,semantics-based method,text document,traditional chinese medicine text,traditional term frequency method,knowledge engineer,large corpus,knowledge engineering,automatic ontology construction,traditional chinese medicine,term frequency,ontology | Ontology (information science),Ontology-based data integration,Ontology alignment,Process ontology,Ontology chart,Computer science,Ontology Inference Layer,Natural language processing,Artificial intelligence,Suggested Upper Merged Ontology,Upper ontology | Conference |
Citations | PageRank | References |
1 | 0.41 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liping Zhou | 1 | 1 | 0.41 |
| Dezheng Zhang | 2 | 10 | 2.87 |
| Xin Chen | 3 | 98 | 9.56 |
| Chengcui Zhang | 4 | 789 | 84.56 |