Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-08-13 Cooperative journals: 《计算机应用研究》
Abstract: In order to effectively supervise the network, quickly and accurately identify the peer-to-peer flow, by analyzing the interaction and behavior characteristics between nodes and nodes, nodes and links in Peer-to-peer network traffic, a method of Peer-to-peer traffic recognition based on network behavior features is proposed by combining clustering method with flow propagation graph method. Firstly, the flow rate of different kinds of network is collected by collecting packet level and flow level statistic feature of network flow, and then the Peer-to-peer flow is identified by using traffic graph. The experimental results show that the proposed method can effectively identify Peer-to-peer network application traffic in backbone network data, and the f1-measure reaches over 95%.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-20 Cooperative journals: 《计算机应用研究》
Abstract: Recommendation system has been widely applied to various types of e-commerce sites, which effectively solved the problem of information overload, collaborative filtering algorithm is the most common in the recommendation system of personalized recommendation technology. Based on the problem of the traditional method of similarity measurement, a hybrid recommendation algorithm is proposed to combine the change of interest and class correlation degree. The algorithm classifies the project according to the user's rating project information, and finds out how much the user likes to pay attention to different categories of projects. At the same time, the time based interest weight function is introduced into the project similarity calculation to further improve the accuracy of calculation. Finally, the improved similarity calculation method is integrated into the user clustering method. After the user clustering, the category of its location will have a great effect on the user's recommended accuracy. The experimental results show that the algorithm is improved in operation efficiency and accuracy in the moviels-1k data set.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-18 Cooperative journals: 《计算机应用研究》
Abstract: In order to measure shape difference of two models accurately, this paper proposed a method for calculating model similarity based on particle swarm. It used edge number of face to construct face similarity matrix, and used particle swarm algorithm to search this matrix to get an optimal face matching sequence between two models. It extracted correspondent face similarity values according to this face matching sequence from face similarity matrix. This paper accumulated face similarities to calculate two models' similarity and measured shape difference of two models. Experimental results show that this method can evaluate similarity between two models accurately.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》
Abstract: Geometric constraint solving is a key technique in CAD modeling. This paper researched the problem that solving quality was not high and solving speed was slow. It proposed a method of geometric constraint solving, which combined fish swarm algorithm and chaos algorithm. Firstly, this paper denoted geometric constraint relations in CAD model as a group of algebraic equations. Secondly, it used this group of algebraic equations to construct objective function. This paper transformed a problem of geometric constraint solving into a problem of objective function optimization. Finally, it used chaos algorithm to improve fish swarm algorithm in order to find an optimal solution of objective function. Experimental results show that this method can effectively solve geometric constraint problems.