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In recent years, with the gradual development of mobile Internet technology, the number of mobile applications increases dramatically. Users facing numerous mobile applications are often caught off guard. It is necessary to automatically classify the applications according to the applications' information, so as to recommend appropriate applications to users. However, the text information directly...
An improved imbalanced AdaBoost algorithm called ImAdaBoost was proposed for four-chamber plane detection in cardiac ultrasound images. By assigning dynamic weight adjustment factor to each sample according the precision and true positive rate of weak learner, imbalanced classification problem was converted to cost-sensitive classification problem. Template matching method was used to detect the degree...
This study aims to explore the determinants influencing usage intention in mobile social media from the user motivation and the Theory of Planned Behavior (TPB) perspectives. Based on TPB, this study added three motivations, namely entertainment, sociality, and information, into the TPB model, and further examined the moderating effect of posters and lurkers in the relationships of the proposed model...
The Twitter System is the biggest social network in the world, and everyday millions of tweets are posted and talked about, expressing various views and opinions. A large variety of research activities have been conducted to study how the opinions can be clustered and analyzed, so that some tendencies can be uncovered. Due to the inherent weaknesses of the tweets - very short texts and very informal...
Microblog, with its wide participation and convenience, has changed the way that people get news about current events. In recent years, lots of breaking news and hot topics are released by microblog platform firstly, as well as its much wider and more distribution than traditional media platform. Extracting these useful information in real-time will help us to grasp the latest and hottest topics which...
With the rapid development of information technology, the concept of big data is used in information collection on different things, especially for the image data. In the image processing field, the identification and classification methods are complex. In this paper, we analyzed the mathematical model of color spaces, convert ordinary human perception of color to a value which is easy to classify...
In recent years, with the development of the Internet, it is more and more common for users to buy mobile phones on the Internet. On the one hand, sentiment analysis help customers to fully understand the performance of the phone, on the other hand, it provides improvement direction for producer to upgrade the goods. In this paper, we use the method of semantic analysis to analyze the sentiment of...
Call center is an important intermediary between enterprise and customers. It not only helps customers to solve the problems they are faced with but also allows the enterprise to deeply analyze the customer's voice and make a distinct market positioning. Nowadays customer satisfaction in call center have been attached much importance and studied extensively. However, few researches are actually about...
Sentiment analysis at home and abroad has been a hot topic, with the development of sina Weibo and Tencent Weibo and other social networking platform, the micro-blog text sentiment analysis has also been more and more attention. Analysis of the emotional micro-blog text is designed to mining user for a product of positive and negative evaluation, in order to analyze the popularity of products. In...
With the successful adoption of Web 2.0 applications, consumers are increasingly voicing their opinions and concerns, and providing suggestions in online review communities. Consumers who significantly influence the opinions and decisions of others through communicative acts are called opinion leaders. These leaders usually capture the most representative opinions and play a crucial role in electronic...
Dimensionality reduction of big data is becoming more and more important in many domains, such as cloud computing, human gene distribution, image processing and smart grids, which all involve high-dimensional data analysis. While traditional linear dimensionality reduction techniques are computationally efficient and simple to implement, they fail to adequately capture the intrinsic structure of complex...
Based on internet of things and communication technology, this paper puts forward the overall architecture of dynamic monitoring system in the high slope and monitoring equipment technology system. High slope monitoring project in Southwest mountain was set an example to propose the dynamic monitoring scheme of the high slope. On the basis of long-term monitoring data, studying the prediction model,...
Heterodyne laser interferometer, which is used as a sensor for high-precision displacement measurement, is used to measure the ground motion and seismic waves as a seismometer. Through the displacement variation obtained by the precision measurement, we predict the magnitude of the earthquake. The Recursive Least Square (RLS) method reduces the error of earthquake magnitude prediction. RLS method...
With the applications of clouds computing and social network, it is of great interests for investors to grasp the variation and predict the trend in stock market. Because of too many factors that affect the stock market, it is quite difficult for a thorough understanding and successful prediction of the variation and the trend of stock market. By retrieving the emotional vocabulary in twitter social...
Data Mining is concerned with the discovery of interesting patterns and knowledge in data repositories. Cluster Analysis which belongs to the core methods of data mining is the process of discovering homogeneous groups called clusters. Given a data-set and some measure of similarity between data objects, the goal in most clustering algorithms is maximizing both the homogeneity within each cluster...
In thermal error modeling, traditional methods of system identification modeling based on modern control theory are influenced unfavourably by the boundedness of modeling information (data) and unmodeled dynamics, so it is difficult to improve the robustness and accuracy of the model. With the appearance of big data, a fresh angle of view, however, is provided for improving the model accuracy and...
The energy-saving research of virtualization of the cloud computing platform shows that there are problems in the management mode of the existing virtualization platform. This model is based on a single node managing the whole platform and the single model is responsible for migrating as well as scheduling all of the virtual machine. The migration scope of virtual machine for these models will be...
Cloud computing is becoming increasingly popular. Information technology market leaders, e.g., Microsoft, Google, and Amazon, are extensively shifting toward cloud-based solutions. However, there is isolation in the cloud implementations provided by the cloud vendors. Limited interoperability can cause one user to adhere to a single cloud provider; thus, a required migration of an application or data...
Elasticity is the key feature of cloud computing technology, which can automatically reduce and add resources to meet users' need. In order to achieve elasticity, we should find how and when to trigger the elasticity automatic scaling mechanism. Workload analyzing is a popular method to solve this problem. In this paper, we propose three models to predict the workload based on analyzing monitoring...
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