Abstract
Scientific and technical information database for electric power becomes indispensable with the development of big data and think tank in electric industry. Querying information database is time-consuming and cache management is an efficient solution. In the paper we focus on a multi-level cache management in order to improve search speed of sci-tech information. The proposed computation method of cached data value considers visiting volume, data size and user experience, which is accurate for choosing key words and caching device. Our caching management framework consists of four modules, and the used machine learning method could effectively predict the number of visits next period for key words. The experiments demonstrate that our proposed MLCM approach performs better in prediction accuracy rate, query time and user experience than traditional statistic, LRU, LFU algorithms.
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