Skip to main content
Springer Nature Link
Log in

The Role of Query Sessions in Extracting Instance Attributes from Web Search Queries

  • Conference paper
Advances in Information Retrieval (ECIR 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5993))

Included in the following conference series:

Abstract

Per-instance attributes are acquired using a weakly supervised extraction method which exploits anonymized Web-search query sessions, as an alternative to isolated, individual queries. Examples of these attributes are top speed for chevrolet corvette, or population density for brazil). Inherent challenges associated with using sessions for attribute extraction, such as a large majority of within-session queries not being related to attributes, are overcome by using attributes globally extracted from isolated queries as an unsupervised filtering mechanism. In a head-to-head qualitative comparison, the ranked lists of attributes generated by merging attributes extracted from query sessions, on one hand, and from isolated queries, on another hand, are about 12% more accurate on average, than the attributes extracted from isolated queries by a previous method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Grishman, R., Sundheim, B.: Message Understanding Conference-6: a brief history. In: Proceedings of the 16th Conference on Computational Linguistics, vol. 1, pp. 466–471 (1996)

    Google Scholar 

  2. Chklovski, T., Gil, Y.: An analysis of knowledge collected from volunteer contributors. In: Proceedings of the National Conference on Artificial Intelligence, p. 564 (2005)

    Google Scholar 

  3. Etzioni, O., Banko, M., Soderland, S., Weld, S.: Open information extraction from the web. Communications of the ACM 51(12) (December 2008)

    Google Scholar 

  4. Sekine, S.: On-demand information extraction. In: Proceedings of the COLING/ACL on Main conference poster sessions, pp. 731–738 (2006)

    Google Scholar 

  5. Banko, M., Cafarella, M.J., Soderland, S., Broadhead, M., Etzioni, O.: Open information extraction from the Web. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007), pp. 2670–2676 (2007)

    Google Scholar 

  6. Tokunaga, K., Kazama, J., Torisawa, K.: Automatic discovery of attribute words from web documents. In: Proceedings of the 2nd International Joint Conference on Natural Language Processing (IJCNLP 2005), Jeju Island, Korea, pp. 106–118 (2005)

    Google Scholar 

  7. Yoshinaga, N., Torisawa, K.: Open-domain attribute-value acquisition from semi-structured texts. In: Proceedings of the Workshop on Ontolex, pp. 55–66 (2007)

    Google Scholar 

  8. Cafarella, M., Halevy, A., Wang, D., Zhang, Y.: Webtables: Exploring the power of tables on the web. Proceedings of the VLDB Endowment archive 1(1), 538–549 (2008)

    Google Scholar 

  9. Wu, F., Hoffmann, R., Weld, D.: Information extraction from Wikipedia: Moving down the long tail. In: Proceedings of the 14th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2008), pp. 731–739 (2008)

    Google Scholar 

  10. Paşca, M., Van Durme, B.: What you seek is what you get: Extraction of class attributes from query logs. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007), pp. 2832–2837 (2007)

    Google Scholar 

  11. Paşca, M.: Organizing and searching the World Wide Web of facts - step two: Harnessing the wisdom of the crowds. In: Proceedings of the 16th World Wide Web Conference (WWW 2007), Banff, Canada, pp. 101–110 (2007)

    Google Scholar 

  12. Pustejovsky, J.: The Generative Lexicon: a Theory of Computational Lexical Semantics. The MIT Press, Cambridge (1991)

    Google Scholar 

  13. Guarino, N.: Concepts, attributes and arbitrary relations. Data and Knowledge Engineering 8, 249–261 (1992)

    Article  Google Scholar 

  14. Schubert, L.: Turing’s dream and the knowledge challenge. In: Proceedings of the 21st National Conference on Artificial Intelligence (AAAI 2006), Boston, Massachusetts (2006)

    Google Scholar 

  15. Bellare, K., Talukdar, P., Kumaran, G., Pereira, F., Liberman, M., McCallum, A., Dredze, M.: Lightly-supervised attribute extraction. In: NIPS 2007 Workshop on Machine Learning for Web Search (2007)

    Google Scholar 

  16. Probst, K., Ghani, R., Krema, M., Fano, A., Liu, Y.: Semi-supervised learning of attribute-value pairs from product descriptions. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007), pp. 2838–2843 (2007)

    Google Scholar 

  17. Silverstein, C., Marais, H., Henzinger, M., Moricz, M.: Analysis of a very large Web search engine query log. In: ACM SIGIR Forum, pp. 6–12 (1999)

    Google Scholar 

  18. Jansen, B., Spink, A., Taksa, I.: Handbook of Research on Web Log Analysis. Information Science Reference (2008)

    Google Scholar 

  19. He, D., Goker, A.: Detecting session boundaries from web user logs. In: Proceedings of the BCS-IRSG 22nd Annual Colloquium on Information Retrieval Research, pp. 57–66 (2000)

    Google Scholar 

  20. Wen, J., Nie, J., Zhang, H.: Clustering user queries of a search engine. In: Proceedings of the International Conference on World Wide Web (2001)

    Google Scholar 

  21. Zhang, Z., Nasraoui, O.: Mining search engine query logs for query recommendation. In: Proceedings of the 15th International Conference on World Wide Web, pp. 1039–1040 (2006)

    Google Scholar 

  22. Church, K., Hanks, P.: Word association norms, mutual information, and lexicography. Computational Linguistics 16(1), 22–29 (1990)

    Google Scholar 

  23. Jones, R., Rey, B., Madani, O., Greiner, W.: Generating query substitutions. In: Proceedings of the 15th International Conference on World Wide Web, pp. 387–396 (2006)

    Google Scholar 

  24. Rey, B., Jhala, P.: Mining associations from Web query logs. In: Proceedings of the Web Mining Workshop, Berlin, Germany (2006)

    Google Scholar 

  25. Xue, G.R., Zeng, H.J., Chen, Z., Yu, Y., Ma, W.Y., Xi, W., Fan, W.: Optimizing Web search using Web click-through data. In: CIKM 2004: Proceedings of the 13th ACM International Conference on Information and Knowledge Management, pp. 118–126 (2004)

    Google Scholar 

  26. Ma, H., Yang, H., King, I., Lyu, M.R.: Learning latent semantic relations from clickthrough data for query suggestion. In: Proceeding of the 17th ACM Conference on Information and Knowledge Management, pp. 709–718 (2008)

    Google Scholar 

  27. Lau, T., Horvitz, E.: Patterns of search: Analyzing and modeling web query refinement. In: Proceedings of the International User Modelling Conference (1999)

    Google Scholar 

  28. Jones, R., Klinkner, K.L.: Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs. In: CIKM 2008: Proceeding of the 17th ACM conference on Information and Knowledge Management, pp. 699–708 (2008)

    Google Scholar 

  29. Boldi, P., Bonchi, F., Castillo, C., Donato, D., Gionis, A., Vigna, S.: The query-flow graph: model and applications. In: CIKM 2008: Proceeding of the 17th ACM conference on Information and Knowledge Management, pp. 609–618 (2008)

    Google Scholar 

  30. Baeza-Yates, R., Tiberi, A.: Extracting semantic relations from query logs. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 76–85 (2007)

    Google Scholar 

  31. Shen, D., Qin, M., Chen, W., Yang, Q., Chen, Z.: Mining Web query hierarchies from clickthrough data. In: Proceedings of the National Conference on Artificial Intelligence (2007)

    Google Scholar 

  32. Paşca, M., Van Durme, B.: Weakly-supervised acquisition of open-domain classes and class attributes from web documents and query logs. In: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics (ACL 2008), Columbus, Ohio, pp. 19–27 (2008)

    Google Scholar 

  33. Komachi, M., Makimoto, S., Uchiumi, K., Sassano, M.: Learning semantic categories from clickthrough logs. In: Proceedings of the ACL-IJCNLP 2009 Conference, Short Papers, pp. 189–192 (2009)

    Google Scholar 

  34. Pennacchiotti, M., Pantel, P.: Entity extraction via ensemble semantics. In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (EMNLP 2009), Singapore, pp. 238–247 (2009)

    Google Scholar 

  35. Wang, X., Chakrabarti, D., Punera, K.: Mining broad latent query aspects from search sessions. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 867–876 (2009)

    Google Scholar 

  36. Wong, T., Lam, W.: An unsupervised method for joint information extraction and feature mining across different web sites. Data & Knowledge Engineering 68(1), 107–125 (2009)

    Article  Google Scholar 

  37. Ravi, S., Paşca, M.: Using structured text for large-scale attribute extraction. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM 2008), pp. 1183–1192 (2008)

    Google Scholar 

  38. Suchanek, F., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge unifying WordNet and Wikipedia. In: Proceedings of the 16th World Wide Web Conference (WWW 2007), Banff, Canada, pp. 697–706 (2007)

    Google Scholar 

  39. Nastase, V., Strube, M.: Decoding Wikipedia categories for knowledge acquisition. In: Proceedings of the 23rd National Conference on Artificial Intelligence (AAAI 2008), Chicago, Illinois, pp. 1219–1224 (2008)

    Google Scholar 

  40. Wu, F., Weld, D.: Automatically refining the Wikipedia infobox ontology. In: Proceedings of the 17th World Wide Web Conference (WWW 2008), Beijing, China, pp. 635–644 (2008)

    Google Scholar 

  41. Raju, S., Pingali, P., Varma, V.: An unsupervised approach to product attribute extraction. In: Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval, pp. 796–800 (2009)

    Google Scholar 

  42. Paşca, M., Van Durme, B., Garera, N.: The role of documents vs. queries in extracting class attributes from text. In: Proceedings of the 16th International Conference on Information and Knowledge Management (CIKM 2007), Lisbon, Portugal, pp. 485–494 (2007)

    Google Scholar 

  43. Spink, A., Jansen, B., Wolfram, D., Saracevic, T.: From e-sex to e-commerce: Web search changes. IEEE Computer 35(3), 107–109 (2002)

    Google Scholar 

  44. Hogan, K.: Interpreting hitwise statistics on longer queries. Technical report, Ask.com (2009)

    Google Scholar 

  45. Barr, C., Jones, R., Regelson, M.: The linguistic structure of english web-search queries. In: Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pp. 1021–1030 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Google Inc,  

    Marius Paşca, Enrique Alfonseca, Enrique Robledo-Arnuncio, Ricardo Martin-Brualla & Keith Hall

Authors
  1. Marius Paşca
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Enrique Alfonseca
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Enrique Robledo-Arnuncio
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ricardo Martin-Brualla
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Keith Hall
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Adaptive Information Cluster, Dublin City University, Dublin, 9, Ireland

    Cathal Gurrin

  2. The Open University, Walton Hall, MK7 6HF, Milton Keynes, UK

    Yulan He

  3. Microsoft Research Ltd, 7 JJ Thomson Avenue, CB3 0FB, Cambridge, UK

    Gabriella Kazai

  4. Department of Computer Science, University of Essex, Wivenhoe Park, CO4 3SQ, Colchester, UK

    Udo Kruschwitz

  5. The Open University, Walton Hall, Milton Keynes, UK

    Suzanne Little

  6. University of London, London, UK

    Thomas Roelleke

  7. Knowledge Media Institute, The Open University, MK7 6AA, Milton Keynes, UK

    Stefan Rüger

  8. Department of Computing Science, University of Glasgow, 17 Lilybank Gardens, G12 8QQ, Glasgow, UK

    Keith van Rijsbergen

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Paşca, M., Alfonseca, E., Robledo-Arnuncio, E., Martin-Brualla, R., Hall, K. (2010). The Role of Query Sessions in Extracting Instance Attributes from Web Search Queries. In: Gurrin, C., et al. Advances in Information Retrieval. ECIR 2010. Lecture Notes in Computer Science, vol 5993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12275-0_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-12275-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12274-3

  • Online ISBN: 978-3-642-12275-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy