2007 · 16 citations · 3 references
ComputingComputer ScienceInformation SystemsData MiningInformation RetrievalNatural Language ProcessingKernel MethodsRetrieval ModelsSearch SystemsService DiscoveryText Similarity AnalysisWeb SearchInformation Retrieval Similarity MetricsKernel-based MatchingSemantic Textual SimilarityService Similarity AnalysisServices SimilaritySimilarity LearningSimilarity MetricsWeb Services
This paper describes a kernel based Web Services (abbrevi-ated as service) matching mechanism for service discoveryand integration. The matching mechanism tries to exploitthe latent semantics by the structure of services. Using textual similarity and n-spectrum kernel values as features of low-level and mid-level, we build up a model to estimate thefunctional similarity between services, whose parameters arelearned by a Ranking-SVM. The experiment results showedthat several metrics for the retrieval of services have beenimproved by our approach.
3
Searching XML documents via XML fragments
David Carmel, Yoelle Maarek, Matan Mandelbrod et al. · 2003 · 200 citations
Ranking definitions with supervised learning methods