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Keyword extraction is an important application in the area of information technology. Automatic keyword extraction can help people know what is the article primarily talking about without reading the long passage carefully. This paper mainly introduced a keyword extraction algorithm using pagerank on Synonym. Firstly, the content in a single document is represented as a weighted synonym co-occurrence...
An on-line BSE algorithm with an adaptive learning rate is proposed. By indirectly studying one of the existing on-line BSE algorithms based on line predictability, the bound for the optimal learning rate which guarantees the convergence of the algorithm is derived. Based on the analysis results, an on-line algorithm with an adaptive learning rate is presented. Since the learning rates of the existing...
Motion estimation for video coding problem, a prediction based on the triangle - a small cross algorithm. The algorithm is mainly used in small cross on the static template blocks and blocks of small campaign focused search, the search for large sports block with triangle template. With the classic diamond search algorithm and square - diamond search algorithm comparison, the search speed increased...
In linear space, the classical perceptron algorithm is simple and practical. But when concerning the nonlinear space it is severely confined mainly on its signal layer structure. This paper analyzes the geometry characteristic of solve region in the pattern set, and presents a new algorithm based on the solve region. The new algorithm could find the better solve vector in the solve region on condition...
A improved algorithm based on UMHexagonS is proposed in this paper. Experiment results show that, the improved algorithm can improve the search efficiency and reduce the search time by about 14% on average, at the same time, ensure the signal to noise ratio basically unchanged.
The Covering algorithm is proposed by Professor ZhangLing and ZhangBo in the 20th century, which simulates the structure of human learning, building a Constructive Neural Network Learning Model. Covering algorithm has been widely used to solve massive data classification problem, because its performance. The covering classification algorithm has fast learning, high recognition rate, massive data processing...
This paper proposes a fast inter prediction mode decision method for H.264. Motion compensation residuals of macroblock are used to analyze motion characteristics of each portion, and reduce the candidate inter modes to a small subset. Compared with the exhaustive mode search, the proposed method achieves an average 63% reduction in computation time with negligible degradation in visual quality. Compared...
The problem of environmental quality assessment is a pattern recognition problem, and a well-trained ANN can exploit the underlying nonlinear relationships that determine the environmental rating of a region. In this study, we are trying with the neural network model to make an effective analysis for environmental quality assessment. A 4-9-1 three-layer feedforward neural network using the backpropagation...
Optimal assigning jobs to resources is an important problem in grid computing. Now grid scheduling policies are mostly traditional heuristic algorithms for scheduling n independent tasks on m processors in early finishing time. However grids have developed to wide area, heterogeneous and non autonomous environments, business objective also became crucial for the success of the scheduling. Therefore...
As the users of social network sites increases, the types of applications service social network sites provide are becoming more and more. This paper establishes an SNS graph generation model based on social services provided by kaixin.com, which describes the intrinsic relationship of entities (users, groups, applications, posts, and albums) in the site; extracts some rules according to the relationship...
To deploy highly efficient video coding technologies on different hardware platform, complexity adjustable algorithms are required. One of the significant resource consumers is motion estimation (ME). This paper proposes a complexity adjustable algorithm for ME to remedy this issue. First, we build a mathematic model to indicate that macroblocks (MBs) with intensive motion are worthier of finer searching...
Acquiring new customers in any business is much more expensive than trying to keep the existing ones. Many churn management models have been developed over the years, mostly focusing on prediction accuracy and not considering the range of parameters and processes essential to manage the system as a whole. This study presents CMF (churn management framework), a framework which tries to covers most...
Data mining deals with extracting or mining knowledge from large and infinite amount of stream data. It also handles the data quality with limited volume of disk or memory. In such traditional transaction environment it is impossible to perform frequent items mining because it requires analyzing which item is a frequent one to continuously incoming stream data and which is probable to become a frequent...
Video Compression has played an important role in Multimedia data storage and transmission. Video compression techniques remove spatial as well as temporal redundancy using intra-frame and inter-frame coding respectively. A large level of compression can be achieved through inter-frame coding. In this paper, performance of four matching criterion in the temporal coding of video signal, which are Minimum...
The increasing users and items restrict the development of collaborative filtering recommendation systems. Then a series of problems, such as sparsity, cold start and scalability, come out. In this paper, we add user preference based on item genre, compute the similarity aimed at user preference. It can reduce the amount of data and improve the rapidity when computing similarity between items, and...
A kind of adaptive PID control algorithm is analyzed, and the drawbacks of the existing algorithms are commented. As an improvement, a neural network intelligent control algorithm based on one-step prediction is developed. Result show that the new control method is more adaptable to the control of time-varying and nonlinear control systems.
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