Analysis of large data logs: an application of Poisson sampling on excite web queries
Ozmutlu, H. Cenk, Ozmutlu, Seda, & Spink, Amanda H. (2002) Analysis of large data logs: an application of Poisson sampling on excite web queries. Information Processing and Management, 38(4), pp. 473-490.
Search engines are the gateway for users to retrieve information from the Web. There is a crucial need for tools that allow effective analysis of search engine queries to provide a greater understanding of Web users' information seeking behavior. The objective of the study is to develop an effective strategy for the selection of samples from large-scale data sets. Millions of queries are submitted to Web search engines daily and new sampling techniques are required to bring these databases to a manageable size, while preserving the statistically representative characteristics of the entire data set. This paper reports results from a study using data logs from the Excite Web search engine. We use Poisson sampling to develop a sampling strategy, and show how sample sets selected by Poisson sampling statistically effectively represent the characteristics of the entire dataset. In addition, this paper discusses the use of Poisson sampling in continuous monitoring of stochastic processes, such as Web site dynamics.
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|Item Type:||Journal Article|
|Keywords:||Poisson sampling, Large, scale in depth data analysis, Web user modeling, Search engine queries, Data mining|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2002 Elsevier|
|Copyright Statement:||Reproduced in accordance with the copyright policy of the publisher.|
|Deposited On:||28 Nov 2006|
|Last Modified:||10 Aug 2011 16:41|
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