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Topic detection and tracking (TDT) under modern media circumstances has been dramatically innovated with the ever-changing social network and inconspicuous connections among participants in the internet communities. Apart from the inherent word features of analysing materials, such as news articles and personal or professional comments, incidental information attracts increasing attention from the...
The movie recommendation system provides an important way for users to choose a movie. In order to avoid manmode operations in the movie recommendation, the emotional analysis in the recommended system provides a new way of thinking. The traditional methods were based on knowledge, statistics and the hybrid approach. However these methods could obtain effect only base on the dataset with small amount...
The aim of this paper is to propose a transformation algorithm for multi-granularity linguistic information assessed in different unbalanced linguistic term sets together with its application in linguistic group decision making (LGDM) problem. Assuming that the linguistic information given to the alternatives by different decision makers distribute in different granularity and/or semantic term sets...
People's attitudes towards public events or products may change overtime, rather than staying on the same state. Understanding how sentiments change overtime is an interesting and important problem with many applications. Given a certain public event or product, a user's sentiments expressed in microblog stream can be regarded as a vector. In this paper, we define a novel problem of sentiment evolution...
In order to effectively integrate and share the enormous dispersed digital media resources, we propose Digital Media Cloud (DMCloud), aiming to integrate and share the distributed digital media resources and provide digital media synthesis services. In this paper, we construct a conceptual prototype for DMCloud. Firstly, we build a digital media resource unified view to manage resources, and develop...
Many real-world Web mining tasks need to discover topics interactively, which means the users are likely to interfere the topic discovery and selection processes by expressing their preferences. In this paper, a new algorithm based on Latent Dirichlet Allocation (LDA) is proposed for interactive topic evolution pattern detection. To eliminate those topics not interested, it allows the users to add...
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