Chinese Sentiment Classification Using Extended Word2Vec

Sentiment analysis is now more and more important in modern natural language processing,and the sentiment classification is the one of the most popular applications.The crucial part of sentiment classification is feature extraction.In this paper,two methods for feature extraction,feature selection and feature embedding,are compared.Then Word2Vec is used as an embedding method.In this experiment,Chinese document is used as the corpus,and tree methods are used to get the features of a document:average word vectors,Doc2Vec and weighted average word vectors.After that,these samples are fed to three machine learning algorithms to do the classification,and support vector machine(SVM) has the best result.Finally,the parameters of random forest are analyzed.

Impacts and uncertainty analysis of elevated temperature and CO_2 concentration on wheat biomass

Impacts of climatic change on agriculture and adaptation are of key concern of scientific research. However, vast uncertainties exist among global climates model output, emission scenarios, scale transformation and crop model parameterization. In order to reduce these uncertainties, we integrate output results of four IPCC emission scenarios of A1 FI, A2, B1 and B2, and five global climatic patterns of HadCM3, PCM, CGCM2, CSIRO2 and ECHAM4 in this study. Based on 20 databases of future climatic change scenarios from the Climatic Research Unit （CRU） , the scenario data of the climatic daily median values are generated on research sites with the global mean temperature increase of 1℃（GMT＋ID）, 2℃（GMT＋2D） and 3℃（GMT＋3D）. The impact of CO2 fertilization effect on wheat biomass for GMT＋I D, GMT＋2D and GMT＋3D in China＇s wheat-producing areas is studied in the process model, CERES-Wheat and probabilistic forecasting method. The research results show the CO2 fertilization effect can compensate reduction of wheat biomass with warming temperature in a strong compensating effect. Under the CO2 fertilization effect, the rain-fed and irrigated wheat biomasses increase respectively, and the increment of biomass goes up with temperature rising. The rain-fed wheat biomass increase is greater than the irrigated wheat biomass. Without consideration of CO2 fertilization effect, both irrigated and rain-fed wheat biomasses reduce, and there is a higher probability for the irrigated wheat biomass than that of the rain-fed wheat biomass.