Name
Abstract | ||
|---|---|---|
The existed methods of association rules retrieval have not given enough high-level semantic information retrieval support. In order to resolve this problem, the authors propose a new method of association rules retrieval that is based on ontology and semantic Web. Ontology-based association rules retrieval method can well deal with the problems of rule semantics sharing, rule semantics consistency and intelligibility. The authors discuss the ontology-based association rules retrieval method in detail and implement a prototype system called O-ARR using Protege tools. In this paper, the system architecture of O-ARR is firstly brought forward, and then the retrieval methods of O-ARR are listed and discussed. Several key issues of O-ARR, which include establishment of rule retrieval ontology, annotation of ontology instance, query parse and user interface, are analyzed. The method also gives a technique support for further rule information utilization, such as rule information automatic analysis and intelligent reasoning |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICDMW.2006.126 | ICDM Workshops |
Keywords | Field | DocType |
rule semantics,protege tools,query parse,ontologybased association rules retrieval,rule semantics sharing,rule information automatic analysis,semantic information retrieval support,intelligent reasoning,rule information utilization,high-level semantic information retrieval,information retrieval,rule retrieval ontology,rule semantics consistency,o-arr,user interface,ontology-based association rules retrieval,semantic web,ontologies (artificial intelligence),data mining,technique support,association rules retrieval,retrieval method,association rule,system architecture | Ontology (information science),Data mining,Cognitive models of information retrieval,Human–computer information retrieval,Information retrieval,Computer science,Image retrieval,Relevance (information retrieval),Upper ontology,Semantic Web Rule Language,Concept search | Conference |
ISBN | Citations | PageRank |
0-7695-2702-7 | 2 | 0.37 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Shen | 1 | 431 | 34.86 |
| Min Yao | 2 | 25 | 3.82 |
| Zhaohui Wu | 3 | 3121 | 246.32 |
| Yangu Zhang | 4 | 2 | 2.40 |
| Wensheng Yi | 5 | 11 | 1.70 |