Name
Title | ||
|---|---|---|
Improving Performance of Web Services Query Matchmaking with Automated Knowledge Acquisition |
Abstract | ||
|---|---|---|
There is a critical need to design and develop tools that abstract away the fundamental complexity of XML-based Web services specifications and toolkits, and provide an elegant, intuitive, simple, and powerful query-based invocation system to end users. Web services based tools and standards have been designed to facilitate seamless integration and development for application developers. As a result, current implementations require the end user to have intimate knowledge of Web services and related toolkits, and users often play an informed role in the overall Web services execution process. We employ a self-learning mechanism and a set of algorithms and optimizations to match user queries with corresponding operations in Web services. Our system uses Semantic Web concepts and Ontologies in the process of automating Web services matchmaking. We present performance analysis of our system and quantify the exact gains in precision and recall due to the knowledge acquisition algorithms. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/WI.2007.66 | Web Intelligence |
Keywords | Field | DocType |
knowledge acquisition algorithm,overall web services execution,intimate knowledge,web services,powerful query-based invocation system,ontology,web services matchmaking,semantic web concept,semantic web,xml-based web services specification,end user,related toolkits,web service,improving performance,automated knowledge acquisition,web services query matchmaking,matchmaking,information extraction,ontologies,owl,computer science,data mining,application development | Services computing,Data mining,World Wide Web,Semantic Web Stack,Computer science,Web standards,WS-I Basic Profile,Data Web,Web modeling,Web service,WS-Policy | Conference |
ISBN | Citations | PageRank |
0-7695-3026-5 | 10 | 0.67 |
References | Authors | |
9 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chaitali Gupta | 1 | 20 | 3.84 |
| Rajdeep Bhowmik | 2 | 21 | 4.21 |
| Michael R. Head | 3 | 114 | 11.13 |
| Madhusudhan Govindaraju | 4 | 854 | 96.53 |
| Weiyi Meng | 5 | 2722 | 514.77 |