NDLI: An Intersection Cache Based on Frequent Itemset Mining in Large Scale Search Engines

Content Provider	IEEE Xplore Digital Library
Author	Wanwan Zhou Ruixuan Li Xinhua Dong Weijun Xiao Zhiyong Xu
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Virginia Commonwealth Univ., Richmond, VA, USA (Weijun Xiao) \|\| Dept. of Math. & Comput. Sci., Suffolk Univ., Boston, MA, USA (Zhiyong Xu) \|\| Sch. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China (Wanwan Zhou; Ruixuan Li; Xinhua Dong)
Abstract	Caching is an effective optimization in large scale web search engines, which is to reduce the underlying I/O burden of storage systems as far as possible by leveraging cache localities. Result cache and posting list cache are popular used approaches. However, they cannot perform well with long queries. The policies used in intersection cache are inefficient with poor flexibility for different applications. In this paper, we analyze the characteristics of query term intersections in typical search engines, and present a novel three-level cache architecture, called TLMCA, which combines the intersection cache, result cache, and posting list cache in memory. In TLMCA, we introduce an intersection cache data selection policy based on the Top-N frequent itemset mining, and design an intersection cache data replacement policy based on incremental frequent itemset mining. The experimental results demonstrate that the proposed intersection cache selection and replacement policies used in TLMCA can improve the retrieval performance by up to 27% compared to the two-level cache.
Starting Page	19
Ending Page	24
File Size	328499
Page Count	6
File Format	PDF
ISBN	9781467396882
DOI	10.1109/HotWeb.2015.17
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	cache Itemsets intersection cache Heuristic algorithms search engine Computer architecture Search engines Hard disks Data mining Indexes frequent itemset mining
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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