Automated Identification of Web Queries using Search Type Patterns

Alaa Mohasseb, Maged El-Sayed, Khaled Mahar

Abstract

The process of searching and obtaining information relevant to the information needed have become increasingly challenging. A broad range of web queries classification techniques have been proposed to help in understanding the actual intent behind a web search. In this research, we are introducing a new solution to automatically identify and classify the user's queries intent by using Search Type Patterns. Our solution takes into consideration query structure along with query terms. Experiments show that our approach has a high level of accuracy in identifying different search types.

References

  1. Ashkan, A., Clarke, C. L.,Agichtein, E., &Guo, Q., 2009. Classifying and characterizing query intent.InAdvances in Information Retrieval (pp. 578- 586).Springer Berlin Heidelberg.
  2. Broder, A., 2002.A taxonomy of web search.In ACM Sigir forum (Vol. 36, No. 2, pp. 3-10). ACM.
  3. Bhatia, S., Brunk, C., &Mitra, P., 2012. Analysis and automatic classification of web search queries for diversification requirements. Proceedings of the American Society for Information Science and Technology, 49(1), 1-10.
  4. Baeza-Yates, R., Calderón-Benavides, L., & GonzálezCaro, C., 2006.The intention behind web queries.InString processing and information retrieval (pp. 98-109).Springer Berlin Heidelberg.
  5. Beitzel, S. M., Jensen, E. C., Frieder, O., Grossman, D., Lewis, D. D., Chowdhury, A., &Kolcz, A., 2005. Automatic web query classification using labeled and unlabeled training data. In Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval (pp. 581-582). ACM.
  6. Choo, C. W., Detlor, B., & Turnbull, D., 2000. Information seeking on the Web: An integrated model of browsing and searching. firstmonday, 5(2).
  7. Calderón-Benavides, L., Gonzalez-Caro, C., & BaezaYates, R., 2010. Towards a deeper understanding of the user's query intent. In SIGIR 2010 Workshop on Query Representation and Understanding (pp. 21-24).
  8. Hernández, D. I., Gupta, P., Rosso, P., & Rocha, M. A., 2012.Simple Model for Classifying Web Queries by User Intent.
  9. Jansen, B. J., & Booth, D., 2010. Classifying web queries by topic and user intent. In CHI'10 Extended Abstracts on Human Factors in Computing Systems (pp. 4285- 4290). ACM.
  10. Jansen, B. J., Booth, D. L., & Spink, A., 2008. Determining the informational, navigational, and transactional intent of Web queries. Information Processing & Management, 44(3), 1251-1266.
  11. Kathuria, A., Jansen, B. J., Hafernik, C., &Spink, A., 2010. Classifying the user intent of web queries using k-means clustering. In Internet Research, 20(5), 563- 581.
  12. Kellar, M., Watters, C., & Shepherd, M., 2006.A Goalbased Classification of Web Information Tasks.Proceedings of the American Society for Information Science and Technology, 43(1), 1-22.
  13. Liu, Y., Zhang, M., Ru, L., & Ma, S., 2006. Automatic query type identification based on clickthrough information. In Information Retrieval Technology (pp. 593-600).Springer Berlin Heidelberg.
  14. Lee, U., Liu, Z., & Cho, J., 2005.Automatic identification of user goals in web search.InProceedings of the 14th international conference on World Wide Web (pp. 391-400). ACM.
  15. Lewandowski, D., 2006. Query types and search topics of German Web search engine users. Information Services and Use, 26(4), 261-269.
  16. Lewandowski, D., Drechsler, J., & Mach, S., 2012. Deriving query intents from web search engine queries. Journal of the American Society for Information Science and Technology, 63(9), 1773- 1788.
  17. Mendoza, M., & Zamora, J., 2009. Identifying the intent of a user query using support vector machines. In String Processing and Information Retrieval (pp. 131- 142). Springer Berlin Heidelberg.
  18. Morrison, J. B., Pirolli, P., & Card, S. K., 2001, March. A taxonomic analysis of what World Wide Web activities significantly impact people's decisions and actions. In CHI'01 extended abstracts on Human factors in computing systems (pp. 163-164). ACM.
  19. Rose, D. E., Levinson, D., 2004. Understanding user goals in web search. In Proceedings of the 13th international conference on World Wide Web (pp. 13- 19). ACM.
  20. Wu, D., Zhang, Y., Zhao, S., & Liu, T., 2010. Identification of Web Query Intent Based on Query Text and Web Knowledge. In Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on (pp. 128-131). IEEE.
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Paper Citation


in Harvard Style

Mohasseb A., El-Sayed M. and Mahar K. (2014). Automated Identification of Web Queries using Search Type Patterns . In Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST, ISBN 978-989-758-024-6, pages 295-304. DOI: 10.5220/0004849402950304


in Bibtex Style

@conference{webist14,
author={Alaa Mohasseb and Maged El-Sayed and Khaled Mahar},
title={Automated Identification of Web Queries using Search Type Patterns},
booktitle={Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,},
year={2014},
pages={295-304},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004849402950304},
isbn={978-989-758-024-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,
TI - Automated Identification of Web Queries using Search Type Patterns
SN - 978-989-758-024-6
AU - Mohasseb A.
AU - El-Sayed M.
AU - Mahar K.
PY - 2014
SP - 295
EP - 304
DO - 10.5220/0004849402950304