{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mataws-a-multimodal-approach-for-automatic-ws","title":"MATAWS: A Multimodal Approach for Automatic WS Semantic Annotation","arxiv_id":"1305.0194","date":"2013-05-01","proceeding":null,"authors":["Cihan Aksoy","Vincent Labatut","Chantal Cherifi","Jean-François Santucci"],"abstract":"Many recent works aim at developing methods and tools for the processing of\nsemantic Web services. In order to be properly tested, these tools must be\napplied to an appropriate benchmark, taking the form of a collection of\nsemantic WS descriptions. However, all of the existing publicly available\ncollections are limited by their size or their realism (use of randomly\ngenerated or resampled descriptions). Larger and realistic syntactic (WSDL)\ncollections exist, but their semantic annotation requires a certain level of\nautomation, due to the number of operations to be processed. In this article,\nwe propose a fully automatic method to semantically annotate such large WS\ncollections. Our approach is multimodal, in the sense it takes advantage of the\nlatent semantics present not only in the parameter names, but also in the type\nnames and structures. Concept-to-word association is performed by using Sigma,\na mapping of WordNet to the SUMO ontology. After having described in details\nour annotation method, we apply it to the larger collection of real-world\nsyntactic WS descriptions we could find, and assess its efficiency.","url_abs":"http://arxiv.org/abs/1305.0194v1","url_pdf":"http://arxiv.org/pdf/1305.0194v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"mataws-a-multimodal-approach-for-automatic-ws","repo_url":"https://github.com/CompNet/mataws","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}