Mitsuteru Shiba

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We propose a method for accurate combining of evidence supplied by multiple individual matchers regarding whether two data schema elements match (refer to the same object or concept), or not, in the field of automatic schema matching. The method uses a Bayesian network to model correctly the statistical correlations between the similarity values produced by(More)
Recently, utilizing ICT is a key of success in every field of industries, and its importance is growing more and more. Typical example is introducing ERP software which assists decision making of stakeholders by providing data regarding running business such as supply chain, procurement, inventory, finance, product lifecycle, projects, human resources, and(More)
This paper proposes a novel smoothing model with a combinatorial optimization scheme for all-words word sense disambiguation from untagged corpora. By generalizing discrete senses to a continuum, we introduce a smoothing in context-sense space to cope with data-sparsity resulting from a large variety of linguistic context and sense, as well as to exploit(More)
We address the problem of automating the process of deciding whether two data schema elements match (that is, refer to the same actual object or concept), and propose several methods for combining evidence computed by multiple basic matchers. One class of methods uses Bayesian networks to account for the conditional dependency between the similarity values(More)
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