ABSTRACT
We review a query log of hundreds of millions of queries that constitute the total query traffic for an entire week of a general-purpose commercial web search service. Previously, query logs have been studied from a single, cumulative view. In contrast, our analysis shows changes in popularity and uniqueness of topically categorized queries across the hours of the day. We examine query traffic on an hourly basis by matching it against lists of queries that have been topically pre-categorized by human editors. This represents 13% of the query traffic. We show that query traffic from particular topical categories differs both from the query stream as a whole and from other categories. This analysis provides valuable insight for improving retrieval effectiveness and efficiency. It is also relevant to the development of enhanced query disambiguation, routing, and caching algorithms.
- Beitzel, S., Jensen, E., Chowdhury, A., and Grossman, D. Using Titles and Category Names from Editor-driven Taxonomies for Automatic Evaluation. In Proceedings of CIKM'03 (New Orleans, LA, November, 2003), ACM Press. Google ScholarDigital Library
- Broder, A. A Taxonomy of Web Search. SIGIR Forum 36(2) (Fall, 2002). Google ScholarDigital Library
- Chowdhury, A., G. Pass. "Operational Requirements for Scalable Search Systems", In Proceedings of CIKM'03 (New Orleans, LA, November 2003), ACM Press. Google ScholarDigital Library
- Eastman, C., B. Jansen, "Coverage, Relevance, and Ranking: The Impact of Query Operators on Web Search Engine Results", ACM Transactions on Information Systems, Vol. 21, No. 4, October 2003, Pages 383--411. Google ScholarDigital Library
- Eiron, N., K. McCurley. "Analysis of Anchor Text for Web Search", In Proceedings of SIGIR'03 (Toronto, Canada, July 2003), ACM Press. Google ScholarDigital Library
- Hawking, D., Craswell, N., and Griffiths, K. Which Search Engine is Best at Finding Online Services? In Proceedings of WWW10 (Hong Kong, May 2001), Posters. Actual poster available as http://pigfish.vic.cmis.csiro.au/ nickc/pubs/www10actualposter.pdfGoogle Scholar
- Jansen, B. and Pooch, U. A review of Web searching studies and a framework for future research. Journal of the American Society for Information Science and Technology 52(3), 235--246, 2001. Google ScholarDigital Library
- Jansen, B., Spink, A., and Saracevic, T. Real life, real users, and real needs: a study and analysis of user queries on the web. Information Processing and Management, 36(2) (2000), 207--227. Google ScholarDigital Library
- Jansen, B.J., Goodrum, A., Spink, A. Searching for multimedia: video, audio, and image Web queries. World Wide Web 3(4), 2000. Google ScholarDigital Library
- Lawrence, S. and Giles, C.L. Searching the World Wide Web. Science 280(5360), 98--100, 1998.Google Scholar
- Lempel, R. and Moran, S. Predictive caching and prefetching of query results in search engines. In Proceedings of WWW12 (Budapest, May 2003). Google ScholarDigital Library
- Markatos, E.P. On Caching Search Engine Query Results. In the Proceedings of the 5th International Web Caching and Content Delivery Workshop, May 2000.Google Scholar
- Raghavan, V. and Sever, H. On the Reuse of Past Optimal Queries. In Proc. of the 1995 SIGIR Conference, 344--350, Seattle, WA, July 1995. Google ScholarDigital Library
- Ross, N. and Wolfram, D. End user searching on the Internet: An analysis of term pair topics submitted to the Excite search engine. Journal of the American Society for Information Science 51(10), 949--958, 2000. Google ScholarDigital Library
- Saraiva, P., Moura, E., Ziviani, N., Meira, W., Fonseca, R., Riberio-Neto, B. Rank-preserving two-level caching for scalable search engines. In Proc. of the 24th SIGIR Conference, 51--58, New Orleans, LA, September, 2001. Google ScholarDigital Library
- Silverstein, C., Henzinger, M., Marais, H., and Moricz, M. Analysis of a very large web search engine query log. SIGIR Forum 33(1) (Fall, 1999), 6--12. Google ScholarDigital Library
- Spink, A., Ozmutlu, S., Ozmutlu, H.C., and Jansen, B.J. U.S. versus European web searching trends. SIGIR Forum 36(2), 32--38, 2002. Google ScholarDigital Library
- Spink, A., Jansen, B.J., Wolfram, D., and Saracevic, T. From E-sex to e-commerce: Web search changes. IEEE Computer, 35(3), 107--109, 2002. Google ScholarDigital Library
- Spink, A., Wolfram, D., Jansen, B.J. and Saracevic, T. Searching the Web: The Public and Their Queries. Journal of the American Society of Information Science 53(2), 226--234, 2001. Google ScholarDigital Library
- Spink, A., Jansen, B.J., and Saracevic, T. Vox populi: The public searching of the web. Journal of the American Society of Information Science 52 (12), 1073--1074, 2001. Google ScholarDigital Library
- Spink, A., Jansen, B.J., and Ozmultu, H.C. Use of query reformulation and relevance feedback by Excite users. Internet Research: Electronic Networking Applications and Policy 10 (4), 2000.Google Scholar
- Sullivan, D. Searches Per Day. Search Engine Watch, February, 2003. http://searchenginewatch.com/reports/article.php/2156461Google Scholar
- Wang, P., Berry, M., and Yang, Y. Mining longitudinal web queries: Trends and patterns. Journal of the American Society for Information Science and Technology 54(8), 743--758, June 2003. Google ScholarDigital Library
- J. Wen, J. Nie, H. Zhang "Query Clustering using User Logs" ACM Transactions on Information Systems, Vol. 20, No. 1, January 2002, pp 59--81. Google ScholarDigital Library
- Wolfram, D., H. Xie, "Subject categorization of query terms for exploring Web users' search interests", Journal of the American Society for Information Science, v.53 n.8, p.617--630, June 2002. Google ScholarDigital Library
- Xie, Y., O'Hallaron, D. Locality in Search Engine Queries and Its Implications for Caching. Infocom 2002.Google Scholar
Index Terms
- Hourly analysis of a very large topically categorized web query log
Recommendations
When do people use query suggestion? A query suggestion log analysis
AbstractQuery suggestion, which enables the user to revise a query with a single click, has become one of the most fundamental features of Web search engines. However, it has not been clear what circumstances cause the user to turn to query suggestion. In ...
Temporal analysis of a very large topically categorized Web query log
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 ...
Extracting news-related queries from web query log
WWW '06: Proceedings of the 15th international conference on World Wide WebIn this poster, we present a method for extracting queries related to real-life events, or news-related queries, from large web query logs. The method employs query frequencies and search over a collection of recent news. News-related queries can be ...
Comments