This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few see...
In software development, many kinds of knowledge are shared and reused as software patterns. Howevel; the relation analysis among software by hand is on the large scale. In this w...
Abstract. Gaussian processes have successfully been used to learn preferences among entities as they provide nonparametric Bayesian approaches for model selection and probabilistic...
Social tagging systems provide users with the ability to share information and extend their field of knowledge. The purpose of this paper is to explore the tag relations of user in...