2008 ScalableandNearRealTimeBurstDet

• (Parikh et al., 2008) ⇒ Nish Parikh, and Neel Sundaresan. (2008). “Scalable and Near Real-time Burst Detection from ECommerce Queries.” In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2008). doi:10.1145/1401890.1402006

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%22Scalable+and+near+real-time+burst+detection+from+eCommerce+queries%22+2008
• http://portal.acm.org/citation.cfm?doid=1401890.1402006&preflayout=flat#citedby

Quotes

Abstract

In large scale online systems like Search, eCommerce, or social network applications, user queries represent an important dimension of activities that can be used to study the impact on the system, and even the business. In this paper, we describe how to detect, characterize and classify bursts in user queries in a large scale eCommerce system. We build upon the approaches discussed in KDD 2002 "Bursty and Hierarchical Structure in Streams" [3] and apply them to a high volume industrial context. We describe how to identify bursts on a near real-time basis, classify them, and apply them to build interesting merchandizing applications.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2008 ScalableandNearRealTimeBurstDet	Nish Parikh Neel Sundaresan			Scalable and Near Real-time Burst Detection from ECommerce Queries				10.1145/1401890.1402006