Ontologies have become the de-facto modeling tool of choice, employed in many applications and prominently in the semantic web. Nevertheless, ontology construction remains a daunting task. Ontological bootstrapping, which aims at automatically generating concepts and their relations in a given domain, is a promising technique for ontology construction. Bootstrapping an ontology based on a set of predefined textual sources, such as web services, must address the problem of multiple, largely unrelated concepts. In this paper, we propose an ontology bootstrapping process for web services. We exploit the advantage that web services usually consist of both WSDL and free text descriptors.
The WSDL descriptor is evaluated using two methods, namely Term Frequency/Inverse Document Frequency (TF/IDF) and web context generation. Our proposed ontology bootstrapping process integrates the results of both methods and applies a third method to validate the concepts using the service free text descriptor, thereby offering a more accurate definition of ontologies. We extensively validated our bootstrapping method using a large repository of real-world web services and verified the results against existing ontologies. The experimental results indicate high precision. Furthermore, the recall versus precision comparison of the results when each method is separately implemented presents the advantage of our integrated bootstrapping approach.
Ontology creation and evolution and in particular on schema matching. Many heuristics were proposed for the automatic matching of schema and several theoretical models were proposed to represent various aspects of the matching process such as representation of mappings between Ontologies. However, all the methodologies described require comparison between existing Ontologies.
The ontology bootstrapping process is based on analyzing a Web service using three different methods, where each method represents a different perspective of viewing the Web service. As a result, the process provides a more accurate definition of the ontology and yields better results. In particular, the Term Frequency/ Inverse Document Frequency (TF/IDF) method analyzes the Web service from an internal point of view, i.e., what concept in the text best describes the WSDL document content. The Web Context Extraction method describes the WSDL document from an external point of view, i.e., what most common concept represents the answers to the Web search queries based on the WSDL content. Finally, the Free Text Description Verification method is used to resolve inconsistencies with the current ontology.
- Data Extraction
- Token Extraction
- Term Frequency/IDF Analysis
- Web context extraction
- Ontology Evolution