1.College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China;
2. Zhejiang Branch of Industrial and Commercial Bank of China, Hangzhou 310009, China
A new vertical search engine object cache optimization strategy was proposed to address the challenges like the changeful of popular objects, the property of query triggered data crawl and so on. A popular object prediction model was proposed based on relationships between objects and their properties in order to predict the tendency of popular object distribution. Since user query and data changed by Poisson process, a procedure to maximize the data freshness and an optimal strategy to distribute and balance resource were proposed. Experimental results show that the increase in time complexity is relative limited, while the average freshness of user query result and the query precision ratio preceded traditional fixed-rate cache strategy．
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