This paper describes the model we designed for the Chinese word segmentation Task of NLPCC 2015. We firstly apply a word-based perceptron algorithm to build the base segmenter. Then, we use a Bootstrap Aggregating model of bagging which improves the segmentation results consistently on the three tracks of closed, semi-open and open test. Considering the characteristics of Weibo text, we also pe...

The concept of a pre-open set in a topological space was introduced by H. H. Corson and E. Michael in 1964 [3]. A subset A of a topological space (X, τ) is called pre-open or locally dense or nearly open if A ⊆ Int(Cl(A)). A set A is called pre-closed if its complement is preopen or equivalently if Cl(Int(A)) ⊆ A. The term, pre-open, was used for the first time by A. S. Mashhour, M. E. Abd El-M...

Open set classification (OSC) tackles the problem of determining whether data are in-class or out-of-class during inference, when only provided with a examples at training time. Traditional OSC methods usually train discriminative generative models owned data, and then utilize pre-trained to classify test directly. However, these always suffer from embedding confusion problem, i.e., partial ins...