中文摘要：

为了解决微博文本特征抽取及特征稀疏问题，提出基于卷积神经网络的微博话题追踪模型（CNN-TTM）．基于微博用户信息，又提出融合微博用户信息及卷积神经网络的微博话题追踪模型（CNN—userITM），利用微博用户信息提高话题追踪准确率．实验表明，在新浪微博数据集上，CNN—TTM和CNN—userITM分别获得较高的微博话题追踪准确率．

英文摘要：

Aiming at feature sparseness and feature extraction of microblog text, a topic tracking model for Chinese microblog based on convolutional neural network （CNN-TTM） is proposed. Furthermore, user profiles and attributes are incorporated into CNN-TTM and a model called CNN-UserTTM is constructed. The user information of microblog is used to improve the accuracy of topic tracking. The experimental results demonstrate that CNN-TrM and CNN-UserTTM reach a high accuracy respectively on Sina microblog dataset.