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Document classification has attracted increasing attention recently as a result of the ever-increasing amounts of document data on the Internet. In this paper, an efficient document classification algorithm is proposed by combining the ideas of maximum margin criterion (MMC) and minimax probability machine (MPM). Experimental results on three well-known benchmark document datasets demonstrate the...
Document classification has received extensive attention in the past decade due to its wide range applications. To efficiently deal with this problem, a novel document classification algorithm is proposed by using marginal fisher analysis (MFA) and minimax probability machine(MPM). Experimental results on the WebKB data set show that the proposed algorithm achieves much better performance than other...
To efficiently deal with spam mail filtering problem, a novel spam filtering algorithm based on locality pursuit projection (LPP) and least square version of SVM(LS-SVM) is proposed in this paper. The mail message features are first extracted by the LPP algorithm, then the LS-SVM classifier is used to classify mails into spam and legitimate. Experimental results demonstrate that the proposed algorithm...
With the explosive increase in document data on the Internet, classifying documents from document database has become one of the hottest research fields.To efficiently deal with this problem, an efficient document classification algorithm based on kernel locality preserving projection (Kernel LPP) is presented in this paper. Experimental results show that the proposed algorithm outperforms other related...
Document categorization is one of the most crucial techniques to assign the documents of a corpus to a set of previously fixed categories. To efficiently deal with document categorization problem, an efficient document categorization algorithm based on local discriminant embedding (LDE) and memetic algorithm (MA) is proposed in this paper. Extensive experiments on Reuter-21578 demonstrate that the...
With the explosive growth in the Web documents, retrieving document from the large-scale document database has become one of the most active research fields in data mining communities. Thus, developing an efficient document query optimization algorithm to retrieval Web document is of great importance. An efficient document query optimization algorithm based on linear discriminant analysis(LDA) and...
The amount of online document has grown greatly in recent years due to the increase in popularity of the World Wide Web. Thus, developing an efficient document classification method to automatically manipulate Web document is of great importance. A novel memetic algorithm (MA)-based document classification algorithm is presented in this paper. The experimental results show that the proposed algorithm...
With the popularization of the Internet, it is challenging to develop spam filters that can effectively eliminate the increasing volumes of unwanted mails automatically before they enter a user's mailbox. To efficiently solve the spam filtering problems, a spam mail filtering method based on neighborhood preserving embedding (NPE) and support vector machines (SVM) classifier is proposed in this paper...
With the fast expansion of the Internet globally in the last decade, the spam e-mail has become a main problem of the email service for Internet service providers, corporate and private users. To efficiently solve the spam filtering problems, a spam mail filtering method based on locality pursuit projection (LPP) and nearest feature line (NFL) classifier is proposed in this paper. Experimental results...
With the explosive growth of World Wide Web, it is of great importance to develop methods for the automatic classifying of large collections of documents. To efficiently tackle this problem, a novel document classification algorithm based on locality pursuit projection (LPP) and SVM is proposed in this paper. The high-dimensional document space are first mapped into lower-dimensional space with LPP,...
To efficiently deal with Web document classification problem, a novel document classification algorithm based on shuffled frog leaping (SFL) algorithm is proposed in this paper. The SFL algorithm combines the benefits of the genetic-based memetic algorithms and the social behavior-based particle swarm optimization algorithms. The experimental results indicate that the proposed SFL algorithm yields...
With advances in the computer technologies and the rapid development of Internet, information on the Internet is increasing exponentially. To efficiently retrieve relevant documents from the explosive growth of the Internet and other sources of information access, a novel Web document retrieval algorithm based on particle swarm optimization (PSO) and linear discriminant analysis (LDA) algorithm is...
Due to the exponential growth of documents in the Internet and the emergent need to organize them, the automatic document classification has received an ever-increased attention in the recent years. The particle swarm optimization (PSO) algorithm, new to the document classification community, is a robust stochastic evolutionary algorithm based on the movement and intelligence of swarms. In this paper,...
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