Name
Title | ||
|---|---|---|
A Domain Information Retrieval Method based on Pension Insurance Ontology Concept Similarity. |
Abstract | ||
|---|---|---|
Matching key terms is the main method for most engines for information retrieval, but this method cannot meet the needs of people who want to retrieve useful domain information. This is because that it doesn't consider the semantic relation of resources in the context. Ontology is an effective method that can solve the problem of domain knowledge sharing and semantic understanding. In this paper, an optimization strategy is presented for information retrieval domain, and an algorithm is also proposed for ontology concept similarity calculation. Experiments are carried out on the audit guidance system, and the results show that this method significantly improves the accuracy of information retrieval based on domain ontology. © 2013 ACADEMY PUBLISHER. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.4304/jnw.8.12.2908-2914 | JNW |
Keywords | Field | DocType |
concept similarity,domain ontology,information retrieval | Ontology (information science),Semantic similarity,Ontology-based data integration,Data mining,Human–computer information retrieval,Information retrieval,Process ontology,Computer science,Ontology Concept,Suggested Upper Merged Ontology,Upper ontology | Journal |
Volume | Issue | Citations |
8 | 12 | 0 |
PageRank | References | Authors |
0.34 | 15 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qingsheng Wan | 1 | 0 | 1.01 |
| Shaobin Huang | 2 | 11 | 7.93 |
| Kai Sun | 3 | 33 | 7.71 |
| Lifu Feng | 4 | 0 | 0.34 |
| Ya Li | 5 | 0 | 0.34 |