As a classical clustering algorithm, K-means algorithm has a profound research background. In the of big data era, K-means algorithms will play a greater advantage, being able to quickly divide similar data into the s...
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As a classical clustering algorithm, K-means algorithm has a profound research background. In the of big data era, K-means algorithms will play a greater advantage, being able to quickly divide similar data into the same cluster. Combining K-means algorithm with MapReduce distributed computing framework and running on Hadoop big data platform can significantly improve the clustering effect. Based on MapReduce framework structure, this paper studies K-means model, including K-means principle, distance calculation, content validity index and external validity index. On this basis, the K-means clustering flow based on MapReduce big data programmingframework is proposed, and the execution process of the algorithm flow is described in detail, which provides a guide for the algorithm implementation.
Cameras are becoming ubiquitous. Applications including video-based surveillance and emergency response exploit camera networks to detect anomalies in real time and reduce collateral damage. A well-known technique for...
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ISBN:
(纸本)9781479932474;9780769550237
Cameras are becoming ubiquitous. Applications including video-based surveillance and emergency response exploit camera networks to detect anomalies in real time and reduce collateral damage. A well-known technique for detecting anomalies is spatio-temporal analysis - an inferencing technique employed by domain experts (e. g., vision researchers) to answer spatio-temporal queries. In this paper, we propose a distributedframework that facilitates the development and deployment of spatio-temporal analysis applications on large-scale camera networks and backend computing resources. We make the following contributions: (a) an investigation of the computation/communication costs associated with spatio-temporal analysis, (b) a programmingframework designed for large-scale spatio-temporal analysis, and (c) performance evaluations for each step of the spatio-temporal analysis with realistic algorithms.
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