Algorithms for clustering data
Algorithms for clustering data
WordNet: a lexical database for English
Communications of the ACM
The Journal of Machine Learning Research
Term extraction + term clustering: an integrated platform for computer-aided terminology
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Learning domain ontologies for Web service descriptions: an experiment in bioinformatics
WWW '05 Proceedings of the 14th international conference on World Wide Web
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Ontology Learning and Population from Text: Algorithms, Evaluation and Applications
Ontology Learning and Population from Text: Algorithms, Evaluation and Applications
Ontology Matching
Similarity search for web services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Falcon-AO: A practical ontology matching system
Web Semantics: Science, Services and Agents on the World Wide Web
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part II on On the Move to Meaningful Internet Systems
Unsupervised semantic annotation of Web service datatypes
ICCP '10 Proceedings of the Proceedings of the 2010 IEEE 6th International Conference on Intelligent Computer Communication and Processing
Towards the web of concepts: extracting concepts from large datasets
Proceedings of the VLDB Endowment
Ontology learning for cost-effective large-scale semantic annotation of web service interfaces
EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
Toward Semantics Empowered Biomedical Web Services
ICWS '11 Proceedings of the 2011 IEEE International Conference on Web Services
Bootstrapping Ontologies for Web Services
IEEE Transactions on Services Computing
Extracting semantic relationships for web services based on Wikipedia
CSC '11 Proceedings of the 2011 International Conference on Cloud and Service Computing
Web Service Classification Based on Automatic Semantic Annotation and Ensemble Learning
IPDPSW '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum
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The lack of formally expressed semantics in web services complemented with the increasing number of available web services is the main obstacle in analyzing and using the existing web services exposed in the Web. In the absence of appropriate reference domain ontology, annotation of existing web services is dependent on ontology development and ontology learning techniques. In this paper we present an unsupervised ontology learning approach tailored to learning from WSDL documents. The most specific feature of the suggested approach is that it constructs (semi-) automatically ontology fragments from a collection of WSDL documents, that lack any extra textual documentation, by just exploiting element names in the WSDL document. The suggested approach combines both linguistic and statistic analysis techniques such as lexico-syntactic patterns and term co-occurrence analysis. The preliminary results show that the generated ontology captures correctly more than half of the semantic classes and instances as well as taxonomic and non-taxonomic relations, hence, providing a reasonable basis for automatic web services annotation.