An improved Gaussian mixture model （GMM）- based clustering method is proposed for the difficult case where the true distribution of data is against the assumed GMM. First, an improved model selection criterion, the ...An improved Gaussian mixture model （GMM）- based clustering method is proposed for the difficult case where the true distribution of data is against the assumed GMM. First, an improved model selection criterion, the completed likelihood minimum message length criterion, is derived. It can measure both the goodness-of-fit of the candidate GMM to the data and the goodness-of-partition of the data. Secondly, by utilizing the proposed criterion as the clustering objective function, an improved expectation- maximization （EM） algorithm is developed, which can avoid poor local optimal solutions compared to the standard EM algorithm for estimating the model parameters. The experimental results demonstrate that the proposed method can rectify the over-fitting tendency of representative GMM-based clustering approaches and can robustly provide more accurate clustering results.展开更多
Cell-phone short messages in English possess special styles. Some are in a literary style, and others in a non-literary one. In the present paper, the stylistic features of English short messages are illustrated by ap...Cell-phone short messages in English possess special styles. Some are in a literary style, and others in a non-literary one. In the present paper, the stylistic features of English short messages are illustrated by applying the stylistic theory and employing the ＂Model of Analyzing Textual Function＂. The features of the two styles of messages are described and analyzed from the perspectives of their pronunciation, graphology, vocabulary, grammar, discourse, rhetoric, etc., and the stylistic features serve as the basis for discussing the translation principles and methods of English short messages.展开更多
基金The National Natural Science Foundation of China(No.61105048,60972165)the Doctoral Fund of Ministry of Education of China(No.20110092120034)+2 种基金the Natural Science Foundation of Jiangsu Province(No.BK2010240)the Technology Foundation for Selected Overseas Chinese Scholar,Ministry of Human Resources and Social Security of China(No.6722000008)the Open Fund of Jiangsu Province Key Laboratory for Remote Measuring and Control(No.YCCK201005)
文摘An improved Gaussian mixture model （GMM）- based clustering method is proposed for the difficult case where the true distribution of data is against the assumed GMM. First, an improved model selection criterion, the completed likelihood minimum message length criterion, is derived. It can measure both the goodness-of-fit of the candidate GMM to the data and the goodness-of-partition of the data. Secondly, by utilizing the proposed criterion as the clustering objective function, an improved expectation- maximization （EM） algorithm is developed, which can avoid poor local optimal solutions compared to the standard EM algorithm for estimating the model parameters. The experimental results demonstrate that the proposed method can rectify the over-fitting tendency of representative GMM-based clustering approaches and can robustly provide more accurate clustering results.
文摘Cell-phone short messages in English possess special styles. Some are in a literary style, and others in a non-literary one. In the present paper, the stylistic features of English short messages are illustrated by applying the stylistic theory and employing the ＂Model of Analyzing Textual Function＂. The features of the two styles of messages are described and analyzed from the perspectives of their pronunciation, graphology, vocabulary, grammar, discourse, rhetoric, etc., and the stylistic features serve as the basis for discussing the translation principles and methods of English short messages.
