Integrating content centric networking and web content mining: A future efficient internet architecture for healthcare

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Abstract

Healthcare Information Systems are indispensible and require more collaboration nowadays. Network Infrastructure for communication requires extreme bandwidth for doctors’ diagnosis reports and medical images in order to interchange between various hospitals. The recent Internet architecture is a hostcentric network that is less appropriate for healthcare applications in terms of patient monitoring and emergency services. With an emergent use of various interactive healthcare applications, the host-centric networking approach is supposed to be less proficient as it relies on the physical location. Therefore, a new approach to networking architecture called Content-Centric Network (CCN) is considered as the prospective Internet architecture for future. It uses name of data to access the contents rather than location. It reduces the network congestion and traffic by improving the delivery speed. CCN is still less efficient due to unavailability of appropriate content in Content Servers. For this purpose, Web Content Mining (WCM) techniques can facilitate to efficiently perform the data management of CCN. Therefore, this paper contributes: Firstly, by identifying the challenges of WCM such as language independency, structure flexibility, performance, dynamicity, redundancy handling, intelligence and relevant content retrieval. Secondly, it maps identified challenges on WCM techniques to adopt most suitable WCM approach for CCN. Finally, this paper introduces an innovative Internet architecture for healthcare by integrating CCN and WCM to deal the data management issues. From Information Centric Networks (ICN), we have opted CCN for our proposed architecture. While from WCM, Agent-based approach is selected in order to locate most relevant healthcare data.

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APA

Bashir, R., & Akbar, S. (2015). Integrating content centric networking and web content mining: A future efficient internet architecture for healthcare. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9441, pp. 225–236). Springer Verlag. https://doi.org/10.1007/978-3-319-25660-3_19

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