• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.255-265
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• 2007

In this paper we analyzed regularity of daily patterns of distribution of Queries coming from internet search engine. And then, we proposed a Pareto distribution and Zipf law for identifying the query distribution and applied them to daily queries on the search engine during 2 week. We found that there is some evidence that Pareto and Zipf laws can be applied to evaluate the regularity of daily patterns of distribution of queries in search engine. Those results can be used to provide a better understanding of the social interests and trends using the query distribution patterns.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.209-228
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• 2011

Web search behavior has evolved. People now search using many diverse information devices in various situations. To monitor these scattered and shifting search patterns, an improved way of learning and analysis are needed. Traditional web search studies relied on the server transaction logs and single query instance analysis. Since people use multiple smart devices and their searching occurs intermittently through a day, a bundled query research could look at the whole context as well as penetrating search needs. To observe and analyze bundled queries, we developed a proprietary research software set including a log catcher, query bundling tool, and bundle monitoring tool. In this system, users' daily search logs are sent to our analytic server, every night the users need to log on our bundling tool to package his/her queries, a built in web survey collects additional data, and our researcher performs deep interviews on a weekly basis. Out of 90 participants in the study, it was found that a normal user generates on average 4.75 query bundles a day, and each bundle contains 2.75 queries. Query bundles were categorized by; Query refinement vs. Topic refinement and 9 different sub-categories.