Temporal analysis of a very large topically categorized Web query log.

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Bibliographic Details
Title:	Temporal analysis of a very large topically categorized Web query log.
Authors:	Beitzel, Steven M.¹ steve@ir.iit.edu, Jensen, Eric C.¹ ej@ir.iit.edu, Chowdhury, Abdur¹ abdur@ir.iit.edu, Frieder, Ophir¹ ophir@ir.iit.edu, Grossman, David¹ dagr@ir.iit.edu
Source:	Journal of the American Society for Information Science & Technology. Jan2007, Vol. 58 Issue 2, p166-178. 13p. 4 Charts, 24 Graphs.
Subjects:	Internet questionnaires, World Wide Web, Internet searching, Information storage & retrieval systems, Information retrieval, Database searching, Editors, Information science
Abstract:	The authors review a log of billions of Web queries that constituted the total query traffic for a 6-month period of a general-purpose commercial Web search service. Previously, query logs were studied from a single, cumulative view. In contrast, this study builds on the authors' previous work, which showed changes in popularity and uniqueness of topically categorized queries across the hours in a day. To further their analysis, they examine query traffic on a daily, weekly, and monthly basis by matching it against lists of queries that have been topically precategorized by human editors. These lists represent 13% of the query traffic. They show that query traffic from particular topical categories differs both from the query stream as a whole and from other categories. Additionally, they show that certain categories of queries trend differently over varying periods. The authors key contribution is twofold: They outline a method for studying both the static and topical properties of a very large query log over varying periods, and they identify and examine topical trends that may provide valuable insight for improving both retrieval effectiveness and efficiency. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	The authors review a log of billions of Web queries that constituted the total query traffic for a 6-month period of a general-purpose commercial Web search service. Previously, query logs were studied from a single, cumulative view. In contrast, this study builds on the authors' previous work, which showed changes in popularity and uniqueness of topically categorized queries across the hours in a day. To further their analysis, they examine query traffic on a daily, weekly, and monthly basis by matching it against lists of queries that have been topically precategorized by human editors. These lists represent 13% of the query traffic. They show that query traffic from particular topical categories differs both from the query stream as a whole and from other categories. Additionally, they show that certain categories of queries trend differently over varying periods. The authors key contribution is twofold: They outline a method for studying both the static and topical properties of a very large query log over varying periods, and they identify and examine topical trends that may provide valuable insight for improving both retrieval effectiveness and efficiency. [ABSTRACT FROM AUTHOR]
ISSN:	15322882
DOI:	10.1002/asi.20464