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The interactive behavior of Web users often makes some online contents more popular than others. Thus the popularity of online contents can help us understand public interest and attention behind user interactions. Modeling and predicting the popularity of online contents is an important research topic and can facilitate many practical applications in different domains. Previous work on popularity...
Extreme learning machine (ELM) is a simple and effective method of single-hidden layer feedforward neural network. On this basis, there are many other methods are proposed to improve ELM. Weighted extreme learning machine is one of those methods. Weighted ELM is simple in theory and convenient in implementation and it can be applied directly into multiclass classification tasks. This paper improves...
This paper presents the state of art research progress on Chinese single document summarization. Our method utilizes hLDA(hierarchical Latent Dirichlet Allocation) algorithm to model the documents first. A new feature is proposed from the hLDA modeling results, which can reflect some semantic information. Then it combines different traditional features to extract summary sentences from the documents...
Violation vehicle automated snap and road congestion detection play an important role in intelligent transportation system. This article discusses the methods of target detection and recognition in mobile videos. Firstly, a practical method of lane detection based on Hough transforms is put forward. Then a method of target localization under the complex conditions in videos is studied, which is based...
It is interesting but challenging to infer people's personality from multimedia data. This paper resolving this problem by jointly considered both human appearances from portrait image and behavior representative data from social media, where features are designed and selected separately inspired by psychology theory. Best features are selected for four personality categories respectively depending...
Indoor shop recognition can not only help mobile users to quickly recognize a shop to know about the information of interest without needing to enter the shop, but also assist in achieving more accurate user localization in a shopping mall. However, the existing Wi-Fi fingerprint based approaches or image based approaches cannot accomplish this goal well due to the huge cost of constructing large-scale...
Personalized Quality-of-Service (QoS) prediction is an indispensable technique to select suitable services for service-based cloud applications. Considering the dynamic nature of services, efficiently and accurately predicting QoS value becomes an urgent and crucial research issue. In this paper, we propose an online personalized QoS prediction approach for cloud service, namely online learning based...
Intelligent recommendations about where to go will be very helpful for personal and commercial travel recommendations. We deal with this kind of recommendations as a prediction problem based on the tourist's historical visiting sequences and supervised machine learning algorithms, namely Random Forests and LambdaMART. We propose a feature set with 56 dimensions from the tourist's historical traveling...
Information Centric Networking (ICN) is a promising network paradigm for video delivery because of its pervasive in-network caching. However, in ICN, a mobile client at the last hop still suffers buffer starvation due to the wireless bandwidth dynamics and data wastage caused by user cancellation. To address this problem, we propose a Popularity-aware Markov Decision Process (MDP) Approach (called...
Aiming at recovering lost detailed information in low-resolution videos, a novel video super-resolution algorithm based on nonlinear mapping and patch similarity was proposed in this paper. Taking advantage of the strong fitting ability of the convolutional neural network for the nonlinear relationship, this algorithm utilizes the learned reconstruction parameters to pad missing structures and make...
With the rapid development of mobile internet, the number of mobile application on the internet increases every year. The security situation of mobile internet becomes more and more serious. It is necessary to develop an efficient method to detect a mass of mobile applications. In this paper, we analyze the characteristics of mobile application and discover that the relationship between the control...
In recent years, attackers use communication defects among different applications to trigger malicious attack behaviors, we name it combination attack of Android applications. Combination attack of Android applications is researched in depth, but there are still some shortcomings in the research findings. Because the combination attack of Android applications involves several applications, it is more...
With the rapid development of mobile Internet, the functions and scale of mobile intelligent terminal are expanding constantly. The threats of mobile intelligent terminal are gradually revealed. There are a few previous studies on the risk assessment of intelligent terminal. From now on they did not establish an assessment system. Previous studies on the security evaluation of intelligent terminals...
With the prosperity of the mobile network technology, the mobile application security flaw problem brought by the increasingly highlight. Android defects of traditional analysis 20 method only analysis is done in a single software. This plays a limited role on mobile intelligent terminal security. In order to solve this problem, this paper puts forward a mobile application oriented security vulnerability...
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