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In modern web-scale applications that collect data from different sources, entity conflation is a challenging task due to various data quality issues. In this paper, we propose a robust and distributed framework to perform conflation on noisy data in the Microsoft Academic Service dataset. Our framework contains two major components. In the offline component, we train a GBDT model to determine whether...
Traffic in wireless networks has become more diverse due to various applications running on smartphones. Moreover, traffic generated by background processes which has small amount of data and widely dispersed in time takes up a large portion of diverse data applications. To reduce signaling overhead due to frequent state transitions of radio resource control (RRC), the evolved nodeB (eNB) tends to...
We propose Opportunistic Layered Multicasting (OLM), a joint user scheduling and resource allocation algorithm that provides enhanced quality and efficiency for layered video multicast over Mobile WiMAX. This work is a lead off and complete synergy of layered video multicasting with opportunistic concept. The target application is characterized by groups of users acquiring popular video programs over...
A wireless resource scheduling problem is formulated in the context of IPTV multicasting streaming services over WiMAX channels. The goal is to maximize quality of services, in terms of number of subscribers served, number of IPTV channels carried, and video qualities of individual channels; subject to constraints of finite amount of multicast channel capacities as well as time and spatially varying...
We propose a resource allocation algorithm that provides enhanced QoS and efficiency for layered video multicast over mobile WiMAX. The application is characterized by groups of users acquiring popular video programs over a fading channel. To accommodate various bandwidth requirements and adaptive perceptual quality to different users, video streams are coded into base and enhancement layers using...
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