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The amount of information on the Internet is getting larger and larger, and the energy of the consumer and the ability to deal with information is limited. Electricity supplier enterprises in the development process to do are to use big data for personalized shopping guide. This paper analyzes the situation of the development of e-commerce industry in the background of big data, and puts forward the...
The information storm brought about by Big Data is changing our lives, work and thinking, and it's also bringing huge change to the survival environment of enterprises. Decision-making method of enterprises shifts from traditional subjective way to data-driven decision-making methods, precision marketing is becoming the new enterprise marketing tools, and social networks enhance customer satisfaction...
In this investigation we applied the Multi Layer Perceptron (MLP) neural networks for modeling and predicting a real non Gaussian process. The obtained results show that an agreement between predicted and measured values. The statistical error analysis used to evaluate the performance of the correlations, between measured and predicted values provides satisfactory results. The developed model is tested...
In this paper we are interested to applied the adaptive neuro-fuzzy inference system (ANFIS) technique, which is realized by an appropriate combination of fuzzy systems and neural networks, for identifying and forecasting a set of input and output data of packet transmission over internet protocol (IP) networks. The obtained results demonstrate that the developed model presents the same statistical...
In this paper we propose a web log mining-based network user behavior analysis scheme, which plays an important role in network structure optimization and website server configuration. Based on clustering and regression model, we studied the network user's visit model in a university by analyzing a large amount of web log data which is collected from the university campus network. The data analyzing...
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...
Web log files store data related to the use of a website. Analyzing these data in detail is therefore crucial for improving the user browsing experience. However, usually Web log data are stored in flat files in different formats which hinders their analysis, thus obliging to use specific Web log analysis tools. In this context, approaches for structuring Web log data to better analyze them are highly...
The Web has been flooded with highly heterogeneous data sources that freely offer their data to the public. Careful design and compliance to standards is a way to cope with the heterogeneity. However, any agreement and compliance is practically hard to achieve across different communities. In this work we describe a framework that enables the exploitation of content across different scientific disciplines...
Cyberworlds in the era of 'cloud' computing are being created on the Web where data and its dependencies are constantly changing and evolving. The problem of combinatorial explosion in system development inevitably arises when dealing with cyberworlds. To solve the problem, we have developed a data processing system called the Cellular Data System (CDS), based on the Incrementally Modular Abstraction...
As an important technique in modern sociology, social network analysis has gained a lot of attention from many disciplines, and been used as important complements to traditional statistics and data analysis. In order to make it affordable for analysts with massive and fast growing networks, we present X-RIME, a cloud-based library for large scale social network analysis. We propose an implementation-oriented...
In large-scale compute cloud systems, component failures become norms instead of exceptions. Failure occurrence as well as its impact on system performance and operation costs are becoming an increasingly important concern to system designers and administrators. When a system fails to function properly, health-related data are valuable for troubleshooting. However, it is challenging to effectively...
Geospatial data is the core of spatial information system. It is always a research hotspot of how to realize the sharing and integration applications of distributed geospatial data. OGC has developed a number of web services specifications that enable the interoperation of heterogeneous geospatial data sources. Grid is the technology enabling resource sharing and coordinated problem solving in dynamic,...
This paper studies the solution to a kind of data acquisition model, introduces its design principle and architecture, makes a detailed study of its key technology and sums up a kind of method for realizing multi-source data synthesis acquisition, thereby laying a good foundation for the upper data analysis of unified network security management system.
Data(base) reverse engineering is the process through which the missing technical and/or semantic schemas of a database (or, equivalently, of a set of files) are reconstructed. If carefully performed, this process allows legacy databases to be safely maintained, extended, migrated to modern platforms or merged with other, possibly heterogeneous, databases. Although this process is mostly pertinent...
Bayesian networks (BNs) are probabilistic graphical models that are widely used for building diagnosis- and decision-support expert systems. The construction of BNs with the help of human experts is a difficult and time consuming task, which is prone to errors and omissions especially when the problems are very complicated. Learning the structure of a Bayesian network model and causal relations from...
With the evolvement of the Internet and network services, broadband user behavior tends to diversify. It is a rising challenge for the network operators to understand network user behavior. In this paper, we present a general approach for identification and profiling user behavior model by using data mining technique to analyze user activity data. We present analysis of a data set comprised of the...
The Web was an information resource with dynamic state, at the same time, As the spatial data complexity and its multifamily of application field, to get implicit and useful knowledge of space, it is necessary to study the integration issues of the spatial data and choose a suitable technology for data processing and analysis. In the paper, the features of spatial datum were analyzed, they were seriate...
Individual trust development is vital to online collaboration in teams. A semi-virtual case study, which is composed of eight collaborative student groups using Web based computer support, is tracked by the authors over one year. Surveys, interviews and documentation are applied in the data collection. A scale balance model and trust spider diagram are used to analyze the data for all three stages...
By analyzing the characteristics of data sharing between Web applications and the limitations in existing data sharing methods, a new solution for data sharing between Web applications is presented. This data sharing solution transfer data between Web applications directly and provides a much better data sharing experience for the users. We explained this new solution in details from three key aspects...
Web has become the major tool of e-commerce for the last ten years and it requires Internet corporations to provide personalized services by tracking and analyzing users' visiting patterns. Web data analysis system (WDAS) is a necessary tool supporting the Web data mining and knowledge discovery (DM & KD) process. However, in the past, research on DM & KD always focused attention on algorithm...
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