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This paper describes the classical algorithm PageRank, analyzes its existing problems and puts forward improvement of these problems. In the original algorithm, the link similarity and perception of time are added.. Finally an improved PageRank algorithm based on time feedback and topic similarity is proposed. We compared traditional PgageRank algorithm with improved PageRank algorithm by doing some...
Big data technology plays a role in promoting the development of Internet video, and data has become an important carrier for users and network video platform to dig the effect of video communication, guide the video production, and master the user's behavior habits. This system establishes the conceptual process from data acquisition, data processing, data visualization. This article makes analysis...
To solve the issues of user data security and sharing in the cloud storage environment, we studied the methods to build an encrypted cloud storage system with sharing mechanism. This paper provides a method to build such a system on the basis of the existing OpenStack Swift storage service. Then the architecture design of this system is given, which includes the use of the combination of public-key...
This paper presents a TCP/IP-based architecture (IPSecOPEP) to resolve the interoperability issue between PEPs (Performance Enhancing Proxies) and IPSec (Internet Protocol Security). Where this problem is due to the cryptographic protection of TCP header by IPSec ESP protocol, which prohibits TCP enhancing mechanisms to be performed by PEPs. The key idea of this solution is that IPSec devices can...
The existed cloud data models can not well meet the management requirements of structured data including a great deal of relational data, therefore a two-layer cloud data model consisting of a presentation layer and a storage layer is proposed. In the presentation layer, the conception of composite class and composite object are defined to represent the structure and the data of structured data respectively...
Bayesian network (BN), an important machine learning technique, has been widely used in modeling relationships among random variables. BN is considered to be suitable for tasks like prediction, classification and cause analysis. In fact, Bayesian network model often preforms better precision than other commonly used algorithm models in classification and prediction. Meanwhile, taking Max-Min-Hill-Climbing...
This paper defines several metrics to improve network performance, and proposes an approach of two steps to partition domains and deploy controllers for large SDN, reducing the complexity of multiple controller placement model compared with previous works. Firstly, the approach divides the network into several domains based on community detection algorithms. Then, the controllers are deployed in the...
With the development of Kunming's economy and infrastructure construction in China, it's emergency for Kunming bridge and tunnel maintenance departments to improve the level of computerization and the work efficiency. By analyzing WebGIS technology and the business requirements of maintenance departments, this paper presents a design for an inspection and maintenance management system used in urban...
Service deployment is an important phase of aligning business to IT systems in the Service-oriented Architecture (SOA)-based C4ISR system integration. Current methodologies of service deployment mostly focus on system-level service deployment as well as service composition, while the deployment of enterprise-level services to align business processes to IT systems is ignored. This paper deals with...
With the completion of the human genome sequencing, a large number of data especially amino acid sequences floods into biological database. How to analyze these data quickly and even predict the structure and function of protein correctly have become hot topics in recent years. In this paper, we mainly study K-means clustering algorithm and KNN classifier in amino acid sequences of complicated data,...
As a new service-oriented manufacturing paradigm, cloud manufacturing has experienced rapid development in the last few years. It is changing the way manufacturing enterprises organize production activities in that tangible and intangible manufacturing resources encapsulated as virtualized cloud services are provided to customers. However, customers do not know the details of manufacturing service...
In this paper, we design a high-performance data communication message-oriented protocol (ECP), which is based on asynchronous non-blocking I/O model, used reactor design mode, introduced pipeline, and is on top of TCP without modifying the operating system underlying API. It is very effective in the environment that has a great demand of network communication, especially in the case of large-scale...
To deal with the uncertainty of experts' evaluation results on information security risk assessment, this paper proposes a novel evaluation method based on D-S evidence theory and improved TOPSIS. Firstly, the risk matrix is constructed by combining experts' evaluation results with the synthesis of D-S evidence theory based on discount rate. And then, by using improved TOPSIS, this paper solves the...
Nowadays, the amount of the application in Android App Market has grown fast, and the android malwares have been introduced fast into that market, too. In this paper, we use static analysis of a given android application with intensive feature engineering which we focus on different sources and different levels. It means that we not only extract features from the executable file classes.dex but also...
Location-based services have been deep into all aspects of life and it provides a convenient and efficient service experience for people. Currently, technology is relatively mature and widely used in the outdoor positioning. By contrast, for indoor positioning, although there are a lot of hot technology, but they are mostly insufficient lead to it is hard to popularize. So how to improve the popularity...
Software defect prediction is a discipline that predicts the defects proneness of future modules. Software metrics are used for this kind of predication. However, the predication metrics are associated with uncertainty, thus the metrics need to be expressed in linguistic terms to overcome ambiguity and uncertainty. Two types of knowledge are utilized as input to the prediction models: software metrics...
Data mining is an data intelligent analysis technology in the late 20th century, it can automatically extract or find useful model knowledge from large amounts of data in databases, data warehouses or other databases. In this process, the classification of data is an important research topic in the field of data mining. Currently there are different methods for classification, the classification algorithm...
Hyponymy is one of the most critical semantic relations, which contributes magnificently to semantic dictionary, information retrieval etc. In this paper, a method of extracting hyponymy is proposed based on multiple data sources fusion, which convert the extraction of hyponymy to the extraction of hypernyms for target words. First, mining candidate hypernyms for the target words based on search engine,...
Nowadays Spark has been widely adopted as a sharp blade in solving big data problems by pipelining tasks of jobs on each node of cluster. In order to improve cluster resource utilization, lots of Spark performance-tuning advices have been proposed both by Spark and researchers. However, we notice that most of these advices focus tuning configuration items in isolation without considering job characteristics...
human life is more and more dependent on the safety, reliability and effective operation of a variety of complex networks; however, most of networks are sparse, which means the network data is incomplete. To solve the problem, various link prediction methods have been proposed to find missing links in given networks. Among these methods, similarity-based methods are effective, however, still imperfect...
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