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Image classification mainly uses the classifier to classify the extracted image features. In the traditional image feature extraction, it is difficult to set the appropriate feature patterns for the complex images. Simultaneously, the training algorithm of the classifier also affects the accuracy of image classification. In order to solve these problems, the combination of deep belief networks and...
With the rapid development of clustering analysis technology, there have been many application-specific clustering algorithms, such as text clustering. K-Means algorithm, as one of the classic algorithms of clustering algorithms, and a textual document clustering algorithms commonly used in the analysis process, is widely used because of its simple and low complexity. This article in view of two big...
Micro-blog has become the most popular information sharing tool in our daily life. The retweet behavior is a main method of information propagation in micro-blog. So there tweet number prediction not only is an interesting research topic, but also has much practical significance. However, most of current researches only regard this problem as a classification or regression problem, and they did not...
Distribution of data stream is always changed in the real world. This problem is usually defined as concept drift [1]. The state-of-the-art decision tree classification method CVFDT[2] can solve the concept drift problem well, but the efficiency is debased because of its general method of handling instances in CVFDT without considering the types of concept drift. In this paper, an algorithm called...
Vast amount of information is accumulated in many forms during the usage and maintenance of new equipments under information circumstance. The method of data mining is presented in this paper to take full advantage of information and increase scientific decision level of equipment maintenance management. The method includes maintenance information structure analysis, data collection, data coordination,...
With the increasing number of e-commerce sites, how to get a quick search about the information you want from thousands of e-commerce networks is becoming an urgent problem. In this paper, we present a solution to this problem, first, domain knowledge is established according to the e-commerce field, then we build a deep web information retrieval system based on e-commerce to help users find the goods...
With the high development of Internet, e-commerce websites now routinely have to work with log datasets which are up to a few terabytes in size. How to remove messy data timely with low cost and find out useful information is a problem we have to face. The mining process involves several steps from pre-processing the raw data to establishing the final models. In this paper we describe our method to...
Mining of association rules has become an important area in the research on data mining. However the traditional approaches based on support-confidence framework maybe generate a great number of redundant and wrong association rules. In order to solve the problems, a correlation measure is defined and added to the mining algorithm for association rules. According to the value of correlation measure,...
Most previous approaches to automatic audio events (AEs) annotation are based on supervised learning which relies on the availability of a labeled corpus to train classification models. However, instance annotation is often difficult, expensive, and time consuming. In this paper, we apply semi-supervised learning with transductive Support Vector Machine (TSVM) algorithm to automatic AEs annotation...
This article is based on Data mining technology how to apply in the personal credit. Using decision tree algorithm, supporting data processing methods and more potential information for firms in order to facilitate business-to-customer to take a different credit programs.
A knowledge map is a vital tool for better knowledge management. While application of searching the content which user concerned in the website remains in the initial stages of development, website content management is a process of knowledge management and therefore suited to knowledge maps. This paper presents a knowledge map for the intelligentized content website. And in this work it constructs...
An approach to identification of the phishing target of a given (suspicious) webpage is proposed by clustering the webpage set consisting of its all associated webpages and the given webpage itself. We first find its associated webpages, and then explore their relationships to the given webpage as their features for clustering. Such relationships include link relationship, ranking relationship, text...
In high dimensional data space, clusters are likely to exist in different subspaces. K-means is a classic clustering algorithm, but it cannot be used to find subspace clusters. In this paper, an algorithm called GKM is designed to generalize k-means algorithm for high dimensional data. In the objective function of GKM, we associate a weight vector with each cluster to indicate which dimensions are...
As the rapid growth of Internet and the communication link speed, it becomes increasingly challenging for network processors to timely route the incoming traffic to the destination ports. The traditional approach must look up the routing table based on the destination IP address to determine the output port. The ternary CAM approach provides fast associative look up, but is very costly for large routing...
Many time-critical applications, such as emergency evacuation, demand decision-makers to make prompt decisions under time pressure. Therefore, it is essential to design an intuitive and interactive user interface to present critical information to users so that they can make effective decisions in time-critical situation. Using Ajax technology, this paper designs a GIS-based, flexible and interactive...
Speech recognition result is always evaluated by dynamic programming algorithm which can find the best match between recognized results and references. And the match unit could be word, syllable, phone and so on. However, in mandarin speech recognition, this traditional algorithm is not accurate because of the unique characteristics of Chinese word-formation. In order to improve evaluation performance...
Traditional speech recognition methods based on static features of a word to justify whether the word is correctly recognized or not, which neglected the information carried by its contexts and the surrounding environment.In this paper,a 14.1% word error rate (WER) speech recognizer (SR) is used as the baseline system,and 10-dimension static features achived 24.9% decline of Classification Error Rate...
As a new modeling thought, the accurate analytical redundancy model of power plant critical parameters was established by data mining method, which obtained effective information from the large number of real-time operation data. The basic modeling mode, including data preprocessing, mining model, verification model and the strategy from data to analytical redundancy model, was proposed in the paper...
With the merits as far responding distance, hiding receiving and easy-deploying, the single observation passive location has a broad application in military domain and plays an important part in passive radar, navigation and aerospace, etc. With the information of phase-difference, phase-difference rate of change and Doppler frequency rate of change, a new algorithm called PFRC, based on EKF, is proposed...
To solve the security issues in WMN (wireless mesh network), a session key negotiation model based on multi-path in WMN has been proposed, which realizes the pre-detection of Byzantine nodes and prevent the mesh nodes from the man-in-the-middle attacking. Petri net theory is introduced to analyze, in a formalized way, the feature and security of the new model. Solution to the loophole discovered by...
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