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In this paper, a correlation-based clustering hierarchical P2P network model is proposed,which overcomes the problems of poor scalability and low search efficiency in unstructured P2P networks.This model devides the whole unstructured P2P network into clusters formed by a number of nodes through correlation.Each cluster elects a master node to be responsible for managing the entire cluster.The whole...
In order to solve the problem of high dimension in text classification, this paper imported local linear embedding algorithm for dimension reduction. However, the original LLE did not necessarily make the loss of information minimize in process of reduction, so we combinated its two loss function together and improved it firstly. Then, linked the improved LLE and supervised learning and support vector...
It is an urgent problem that how to make synthesis use of various terminals such as mobile phone, PDA etc. to obtain information currently. In allusion to this problem, multi-terminal based proactive information supply system (MPISS) is put forward in this paper. Proactive service is the crucial technology. And it is the core spirit that personalization data can be shared in various terminals. The...
In allusion to the disadvantages that fuzzy c-means algorithm is sensitive to noise and possibilistic c-means is easy to generate superposition cluster center, a novel algorithm (FPCM) which simultaneously produces both memberships and possibilities was proposed in 1997. However, FPCM still uses a norm-induced distance, as a consequence, its performance on the noisy data is not strong enough. In this...
How to describe the knowledge requirement of the user is the precondition of knowledge management. Aiming at the problem, user knowledge requirement model is proposed combining business process with characteristics of the user in the paper. The related information of the task, the related tasks and personal information are considered in the user knowledge requirement model. Knowledge requirement model...
Smart terminal equipments, such as mobile phone, PDA etc., develop quickly at present. At the same time, there is huge information with various formats in the society, such as image, text, table etc. How to obtain information with WAP (Wireless Application Protocol) is an emergency problem nowadays. In allusion to this issue, a study on WAP self-adapt based on Web usage logs is proposed in the paper...
Ontology is a method of expressing knowledge. It is essential for multiple engineers to develop a collaborative ontology. However, current tools, techniques and methodologies for developing collaborative ontology system are inadequate. Against this background, a collaborative ontology development method based on lock-granularity is proposed in this paper. The method aims to control the lock-granularity...
Ontology is an effective method to express knowledge. Some ontologies are large usually. The large scale of ontology brings a new problem in maintenance, release etc. Ontology can be divided into some small ontologies through ontology partition. It leads to easy use of ontology. Ontology partition method based on ant colony algorithm is presented in the paper. Not only hierarchy relations, but also...
How to describe knowledge requirement of the user engaged in work and its change is a critical problem in knowledge management. User knowledge requirement model is proposed by combining business process with personalization in the paper. Key factors and their relation of the user knowledge requirement are described in user knowledge requirement model. User knowledge hybrid evolution algorithm which...
In allusion to the disadvantages that fuzzy c-means algorithm is sensitivity to noise and possibilistic c-means is easy to generate superposition cluster center, interval attributes description based FCM clustering algorithm is proposed in this paper. Firstly, an interval attributes description model of noisy data is presented. Then a clustering algorithm of interval attributes data based on two ends...
A novel method based on support vector machine for coal thickness prediction through seismic attribute technology is proposed in this paper. Based on SVM which embodies the structural risk minimization principle, the proposed method is more generalized in performance and accurate than artificial neural network which embodies the embodies risk minimization principle. In order to improve prediction...
Although the priority and randomicity to initiate clustering centers of K-means have been solved by traditional hierarchical k-means clustering algorithm, the algorithm is difficult to be applied widespread popularly owing to its high computational complexity. So a novel clustering algorithm based on hierarchical and K-means clustering, which has good computational complexity, is proposed in this...
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