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Web GIS is experiencing the development from 2D system to 3D system, and the Web GIS based on VRML is the most popular form of the 3D Web GIS. By analyzing the existing Web GIS system based on VRML, this paper points out its disadvantages and introduces the next generation standard for Web3D - X3D(Extensible 3D specification). A Web GIS model based on X3D is also put forward, which has its own advantages...
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...
Recommendation systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed for the present recommendation systems, such as content-based, collaborative filtering, Web mining-based and so on. But they are always lack of intelligence, self-adaptiveness and initiative. Aiming at these disadvantages, in this work, a personalized...
Color management for the printer is one of the key techniques in the color image reproduction. A New color management model is presented based on analyzing the printer color rendering principle. First, the paper takes standard color target for experimental sample, and substitutes color blocks in color shade district for complete color space to decrease calculation and improve process speed. Second,...
E-learning is a new learning model. Understand the learner's behavior is the foundation of e-learning. This essay present a multi-dimensional and multi-hierarchy model of e-learning behavior, based on this, it designed an E-learning behavior mine system. It used Web Services, data mine and CELTS to implement the system. Through the system, we can master the learner's characteristics and push them...
With increasingly prevalent of E-learning, the intelligent Q/A system arise at the historic moment. In this paper we proposed an improved text cluster algorithm, with the improved association rules algorithm, it can classify the information in the database accurately according to the questions, locate the user's question fast and therefore speeds up the inquiry rate. The experimental result indicates...
The extensive application of association rules in commerce enables itself to be one of the most active research directions in data mining. Recently, the mining of strong correlation item pairs with statistical significance in transaction database receives a certain value. In order to further reduce the cost of testing candidate item pairs in relational database, we have developed the Taper algorithm...
Facial attribute-specific subspace-based PCA (FASS-based PCA) considers the information of class labels, and the discriminant power can be improved. However, it doesn't consider the outliers which are .common in realistic training sets. To address this problem, we propose robust facial attribute-specific subspace-based PCA (robust FASS-based PCA) algorithm in this paper, which gives a new weighted...
With the rapid developing of the network information, it seems to be quite important to provide a more reasonable text classification algorithm for learners. In this paper,we adopt a sensitivity method to modify the characteristic weight in the distance formula and put up with a cutting method of training sample database based on CURE algorithm and Tabu algorithm; then adopt CURE cluster algorithm...
With rapid development of Internet information, It is quite an important project for data mining that how to classify these large amounts of texts. In this paper, we propose an improved text classify cluster algorithm, while calculating similarity, we synthetically consider the relationship between keywords and eigenvector representation on base of term frequency statistics, thereby it lessens sensitivity...
This paper proposes a new data table decomposition algorithm to address problems in extracting rules from massive data tables, e.g. low effectiveness, low computing speed and long rule length. With rough set theory, in the perspective of improving classification correctness and sub data table purity, this paper brings up attribute selection measure, and proposes to stop decomposing process to reduce...
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