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Some companies are willing to execute their business processes (BP) in the cloud for enjoying its benefits. However, they are also reluctant because of the new security risks that using cloud resources introduces. Security risk includes many dimensions, but this work focus on preserving the privacy of the logic of a BP deployed in a multi-cloud context by preventing a coalition of malicious clouds...
Based on the perspective of ensuring business continuity through communication and cooperation between the members, the vulnerability of facility management organization under the interference of emergency was studied. The model and simulation of organization network of facility management based on knowing, emotion, consulting and collaboration relationship was put forward. With the case study, there...
In recent years, network representation learning (NRL) has been increasingly applied into web data analysis, such as video, image and text. Most of NRL methods can widely pursue nodes classification, community detection and link prediction tasks. Due to the nodes in these kinds of networks mostly contain the common attributes and share the same neighbors, we identify them as homogeneous networks,...
A kernel or mini-app is a self-contained small application that retains certain characteristics of the original application [7]. Working on a kernel or mini-app in the place of the original application can dramatically reduce the resources and effort required for performing software tasks such as performance optimization and porting to new platforms. However, using kernel as a proxy is based on the...
Recommendation Systems are an important tool for aiding discovery of content such as movies, books, and music. Generating personalised recommendations that deliver serendipitous suggestions to the user is a key factor in determining user satisfaction. In this paper, we propose a recommendation algorithm that uses a community-structure based link prediction approach. The proposed link prediction algorithm...
Virtual Reality (VR) is poised to revolutionize education by immersing students in learning experiences in a way no other technology has before. In these early days of educational VR applications, it is critical to establish meaningful metrics to determine the potential benefits- and risks-of exposing elementary school students to interactive media using head mounted displays and hand held controllers...
A novel, generic, framework for supporting self-organisation and self-management in hierarchical systems is presented. The framework allows for the incorporation of local self-organising and self-managing strategies at each level in the hierarchy. These local strategies determine the behaviour of that level and the effects of these strategies can be communicated to, and used by, the strategies in...
Recommender systems have proved to be an important response to the information overload problem, by providing users with more proactive and personalized information services. Collaborative filtering is the most popular method in implementing a recommender system. The Slope One algorithm, which is one of collaborative filtering algorithms, is not only easy to implement, but also efficient and effective...
The evaluation of recommender system is often biased towards accuracy, which is hard to balance all participants' interests. In this paper, a novel recommendation strategy using expanded neighbor collaborative filtering (ECF) is presented. Different from the standard collaborative filtering (CF), this recommendation strategy takes into account the second-order neighbors, which are expected to contribute...
Face recognition methods utilizing Sparse Representation based Classification (SRC) and Collaborative Representation based Classification (CRC) have recently attracted a great deal of attention due to inherent simplicity and efficiency. In this paper, we introduce the Large Margin Nearest Neighbor (LMNN), which learns a Mahalanobis distance metric that is applied, to SRC and CRC as the locality constraint...
Users that populate ratings databases, such as IMDB, follow different marking practices, in the sense that some are stricter, while others are more lenient. This aspect has been captured by the most widely used similarity metrics in collaborative filtering, namely the Pearson Correlation and the Adjusted Cosine Similarity, which adjust each individual rating by the mean of the ratings entered by the...
As cloud computing becomes increasingly popular, cloud providers compete to offer the same or similar services over the Internet. Quality of Service (QoS), which describes how well a service is performed, is an important differentiator among functionally equivalent services. As a result, how to help users to find cloud services that meet their QoS requirements becomes an important problem. In this...
As 802.11 network has become an important infrastructure for the Mobile Internet, the performance of WLAN handoff is critical to the quality of user's experience. Although it has shown that there are a large number of invalid handoffs in large-scale 802.11 networks with dense AP, the reason and seriousness still remain unclear. In this paper, we propose HandoffAnalyser, a client-network collaborative...
We study the problem of personalized Quality of Service (QoS) estimation for web services. State-of-the-art methods use matrix factorization or collaborative prediction to estimate web service response times and throughput for each user based on partial measurements collected from past invocations. We point out that in reality, both the response times and through-put of web services follow highly...
We represent a collaborative network as a simplicial complex, which is a collection of sets, with the additional requirement that this collection is closed under the subset operation. Our main objective is to explore ways to guide the evolution of a collaborative network if one has specific design goals in mind that are believed to be essential to the collaboration. For instance, one might wish to...
Objectively quantifying the classification accuracy of Intrusion Detection Systems (IDSs) is of fundamental importance. Evaluation metrics have been proposed to measure the effectiveness of traditional IDSs, but none of those metrics seems suitable to evaluate the distributed collaborative IDSs that are generally employed in Wireless Sensor Networks (WSNs). This is because in WSNs each IDS output...
Developer communication is an important factor during program comprehension. Live programming environments encourage developers to comprehend applications through manipulation of running instances—liveness. Such application exploration is interrupted whenever programmers need to communicate an issue with dislocated co-workers. Describing the issue becomes challenging as programmers use text based...
Analyzing social iterations in a scientific environment will assist researchers in expanding their collaborative networks. Scientific social networks represent the researchers' social iterations in an academic environment. The analysis of these networks requires a detailed study of their structure and it is important the use of visual resources in order to a better understanding of how the social...
Social iterations in the scientific environment can be analyzed to enhance collaboration between researchers. Scientific social networks are complex networks that represent researchers' iterations through academic tasks. Analyzing the structure of those networks researchers can establish new relationships and to understand the potential of collaboration of their relationships. In this paper we use...
With the advent of social networks, micro-blogs have become increasingly popular and recommender systems have been widely used to provide personalized services for better user experience. Traditional collaborative filtering is one of the most popular approaches but it suffers with two well-known problems: cold start and data sparsity. Trust relationships and interaction behaviors in social networks...
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