To properly compute the ontological similarity, an ontological similarity network-based reasoning framework is proposed. It structurally integrates extension-based approach, intension-based approach, the similarity ne...To properly compute the ontological similarity, an ontological similarity network-based reasoning framework is proposed. It structurally integrates extension-based approach, intension-based approach, the similarity network-based reasoning to exploit the implicit similarity, and the feedback from the context to validate the similarity measures. A new similarity measure is also presented to construct concept similarity network, which scales the similarity using the relative depth of the least common super-concept between any two concepts. Subsequently, the graph theory, instead of predefined knowledge rules, is applied to perform the similarity network-based reasoning such that the knowledge acquisition can be avoided. The framework has been applied to text categorization and visualization of high dimensional data. Theory analysis and the experimental results validate the proposed framework.展开更多
We categorify the notion of coalgebras by imposing a co-associative law up to some isomorphisms on the co-multiplication map and requiring that these isomorphisms satisfy certairl law of their own, which is called the...We categorify the notion of coalgebras by imposing a co-associative law up to some isomorphisms on the co-multiplication map and requiring that these isomorphisms satisfy certairl law of their own, which is called the copentagon identity. We also set up a 2-category of 2-coalgebras. The purpose of this study is from the idea of reconsidering the quasi-Hopf algebras by the categorification process, so that we can study the theory of quasi-Hopf algebras and their representations in some new framework of higher category theory in natural ways.展开更多
基金The National Natural Science Foundation of China(No.60003019).
文摘To properly compute the ontological similarity, an ontological similarity network-based reasoning framework is proposed. It structurally integrates extension-based approach, intension-based approach, the similarity network-based reasoning to exploit the implicit similarity, and the feedback from the context to validate the similarity measures. A new similarity measure is also presented to construct concept similarity network, which scales the similarity using the relative depth of the least common super-concept between any two concepts. Subsequently, the graph theory, instead of predefined knowledge rules, is applied to perform the similarity network-based reasoning such that the knowledge acquisition can be avoided. The framework has been applied to text categorization and visualization of high dimensional data. Theory analysis and the experimental results validate the proposed framework.
基金Supported by National Natural Science Foundation of China under Grant Nos. 10975102, 11031005 10871135, 10871227, and PHR201007107
文摘We categorify the notion of coalgebras by imposing a co-associative law up to some isomorphisms on the co-multiplication map and requiring that these isomorphisms satisfy certairl law of their own, which is called the copentagon identity. We also set up a 2-category of 2-coalgebras. The purpose of this study is from the idea of reconsidering the quasi-Hopf algebras by the categorification process, so that we can study the theory of quasi-Hopf algebras and their representations in some new framework of higher category theory in natural ways.
