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In this paper we investigate to what extent the trending topics in Twitter, a popular social network, are manipulated by spammers. Researchers have developed various models for spam detection in social media, but there has been little analysis on the effects of spam on Twitter's trending topics. We gathered over 9 million tweets in Twitter's hourly trending topics over a 7 day period and extracted...
Sparse Bayesian learning (SBL) and relevance vector machines(RVM) have received much attention in the machine learning, which as a means of achieving regression. The methodology relies on a parameterized prior that encourages models with few non-zero weights. In this paper, we present a new and efficient algorithm which exploits properties of the marginal likelihood function to enable maximisation...
In this work, we use Hidden Markov Models (HMM), Conditional Random Field (CRF), Gaussian Mixture Models (GMM) and Mathematical Methods of Statistics (MMS) for Chinese and Japanese text summarization. The purpose of this work is to study the applicability of mentioned three trainable models for cross-language text summarization. For model training, we use several training features such as sentence...
Feature selection methods help machine learning algorithms produce faster and more accurate solutions, because they reduce the input dimensionality and they can eliminate irrelevant or redundant features. Entropy based feature selection algorithms, such as MRMR (Minimum Redundancy Maximum Relevance) and FCBF (Fast Correlation-Based Filter) are preferred feature selection methods because they are very...
The asset valuation is specialized work, and it requests the certified public valuer (CPV) to have the very strong specialized competent ability. Along with the development of the economic in China, the reform of stock system, the tax reform, and the application of fair value in new business accounting standards, the new evaluation domain develops unceasingly, and which sets the new request to the...
In this paper we describe an extension of the information theoretical FCBF (Fast Correlation Based Feature Selection) algorithm. The extension, called FCBF#, enables FCBF to select any given size of feature subset and it selects features in a different order than the FCBF. We find out that the extended FCBF algorithm results in more accurate classifiers.
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