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We study the problem of large-scale social identity linkage across different social media platforms, which is of critical importance to business intelligence by gaining from social data a deeper understanding and more accurate profiling of users. This paper proposes HYDRA, a solution framework which consists of three key steps: (I) modeling heterogeneous(More)
The neural correlates of creativity are poorly understood. Freestyle rap provides a unique opportunity to study spontaneous lyrical improvisation, a multidimensional form of creativity at the interface of music and language. Here we use functional magnetic resonance imaging to characterize this process. Task contrast analyses indicate that improvised(More)
Identifying hot spots of moving vehicles in an urban area is essential to many smart city applications. The practical research on hot spots in smart city presents many unique features, such as highly mobile environments, supremely limited size of sample objects, and the non-uniform, biased samples. All these features have raised new challenges that make the(More)
The neural correlates of narrative production and comprehension remain poorly understood. Here, using positron emission tomography (PET), functional magnetic resonance imaging (fMRI), contrast and functional network connectivity analyses we comprehensively characterize the neural mechanisms underlying these complex behaviors. Eighteen healthy subjects told(More)
Creativity, a multifaceted construct, can be studied in various ways, for example, investigating phases of the creative process, quality of the creative product, or the impact of expertise. Previous neuroimaging studies have assessed these individually. Believing that each of these interacting features must be examined simultaneously to develop a(More)
Modeling is commonly used in the process of software development. UML (Unified Modeling Language) is a standard software modeling language and has been widely adopted for software analysis and design. As software systems are getting larger and more complex nowadays, software modeling using UML often requires collective and collaborative efforts from(More)
With the rapid development of reputation systems in various online social networks, manipulations against such systems are evolving quickly. In this paper, we propose scheme TATA, the abbreviation of joint Temporal And Trust Analysis, which protects reputation systems from a new angle: the combination of time domain anomaly detection and Dempster-Shafer(More)
We consider the problem of super-resolution reconstruction (SRR) in MRI. Subpixel-shifted MR images were taken in several fields of view (FOVs) to reconstruct a high-resolution image. A novel algorithm is presented. The algorithm can be applied locally and guarantees perfect reconstruction in the absence of noise. Results that demonstrate resolution(More)
The problem of unfair testimonies has to be addressed effectively to improve the robustness of reputation systems. We propose an integrated CLUstering-Based approach called iCLUB to filter unfair testimonies for reputation systems using multi-nominal testimonies, in multiagent-based electronic commerce. It adopts clustering and considers buying agents'(More)
Reputation systems have become more and more important in facilitating transactions in online systems. However, the accuracy of reputation systems has always been a concern for the users due to the existence of unfair ratings. Though many approaches have been proposed to mitigate the adverse effect of unfair ratings, most of them use the credibility of the(More)