Skip to main content

Entity Retrieval via Type Taxonomy Aware Smoothing

Part of the Lecture Notes in Computer Science book series (LNISA,volume 10772)

Abstract

We investigate the task of ad-hoc entity retrieval from a knowledge base. We propose a type taxonomy aware smoothing method that exploits the hierarchical type information of a knowledge base and integrates into an existing language modelling framework. Unlike most existing type-aware retrieval models, our approach does not require an explicit inference of query type. Instead, it directly encodes the type information into a term-based retrieval model by considering the occurrence of query terms in multi-fielded pseudo documents of entities whose types have connections in the type taxonomy. We conduct experiments on a recent public benchmark dataset with the Wikipedia category information. Preliminary experiment results show that our framework improves the performance of existing models.

Keywords

  • Entity retrieval
  • Structure-aware smoothing
  • Type taxonomy

The work described in this paper is substantially supported by a grant from the Research Grant Council of the Hong Kong Special Administrative Region, China (Project Code: 14203414).

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-76941-7_75
  • Chapter length: 7 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-76941-7
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   139.99
Price excludes VAT (USA)

References

  1. Neumayer, R., Balog, K., Nørvåg, K.: On the modeling of entities for ad-hoc entity search in the web of data. In: Baeza-Yates, R., de Vries, A.P., Zaragoza, H., Cambazoglu, B.B., Murdock, V., Lempel, R., Silvestri, F. (eds.) ECIR 2012. LNCS, vol. 7224, pp. 133–145. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28997-2_12

    CrossRef  Google Scholar 

  2. Tonon, A., Demartini, G., Cudré-Mauroux, P.: Combining inverted indices and structured search for ad-hoc object retrieval. In: Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 125–134 (2012)

    Google Scholar 

  3. Elbassuoni, S., Blanco, R.: Keyword search over RDF graphs. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, pp. 237–242 (2011)

    Google Scholar 

  4. Neumayer, R., Balog, K., Nørvåg, K.: When simple is (more than) good enough: effective semantic search with (almost) no semantics. In: Baeza-Yates, R., de Vries, A.P., Zaragoza, H., Cambazoglu, B.B., Murdock, V., Lempel, R., Silvestri, F. (eds.) ECIR 2012. LNCS, vol. 7224, pp. 540–543. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28997-2_59

    CrossRef  Google Scholar 

  5. Zhiltsov, N., Kotov, A., Nikolaev, F.: Fielded sequential dependence model for ad-hoc entity retrieval in the web of data. In: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 253–262 (2015)

    Google Scholar 

  6. Hasibi, F., Balog, K., Bratsberg, S. E.: Exploiting entity linking in queries for entity retrieval. In: Proceedings of the 2016 ACM on International Conference on the Theory of Information Retrieval, pp. 209–218 (2016)

    Google Scholar 

  7. Nikolaev, F., Kotov, A., Zhiltsov, N.: Parameterized fielded term dependence models for ad-hoc entity retrieval from knowledge graph. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 435–444 (2016)

    Google Scholar 

  8. Balog, K., Neumayer, R.: Hierarchical target type identification for entity-oriented queries. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, pp. 2391–2394 (2012)

    Google Scholar 

  9. Balog, K., de Vries, A., Serdyukov, P., Westerveld, T., Thomas, P.: Overview of the TREC 2009 entity track (2009)

    Google Scholar 

  10. de Vries, A.P., Vercoustre, A.-M., Thom, J.A., Craswell, N., Lalmas, M.: Overview of the INEX 2007 entity ranking track. In: Fuhr, N., Kamps, J., Lalmas, M., Trotman, A. (eds.) INEX 2007. LNCS, vol. 4862, pp. 245–251. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85902-4_22

    CrossRef  Google Scholar 

  11. Garigliotti, D., Balog, K.: On type-aware entity retrieval. arXiv preprint arXiv:1708.08291. (2017)

  12. Duan, H., Zhai, C.: Exploiting thread structures to improve smoothing of language models for forum post retrieval. In: Clough, P., Foley, C., Gurrin, C., Jones, Gareth J.F., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 350–361. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-20161-5_35

    CrossRef  Google Scholar 

  13. Lu, C., Lam, W., Liao, Y.: Entity retrieval via entity factoid hierarchy. In: ACL, vol. 1, pp. 514–523 (2015)

    Google Scholar 

  14. Chen, Y., Gao, L., Shi, S., Du, X., Wen, J.R.: Improving context and category matching for entity search. In: AAAI, pp. 16–22 (2014)

    Google Scholar 

  15. Hasibi, F., Nikolaev, F., Xiong, C., Balog, K., Bratsberg, S.E., Kotov, A., Callan, J.: DBpedia-entity v2: a test collection for entity search. In: Proceedings of SIGIR, vol. 17 (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xinshi Lin .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Lin, X., Lam, W. (2018). Entity Retrieval via Type Taxonomy Aware Smoothing. In: Pasi, G., Piwowarski, B., Azzopardi, L., Hanbury, A. (eds) Advances in Information Retrieval. ECIR 2018. Lecture Notes in Computer Science(), vol 10772. Springer, Cham. https://doi.org/10.1007/978-3-319-76941-7_75

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-76941-7_75

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76940-0

  • Online ISBN: 978-3-319-76941-7

  • eBook Packages: Computer ScienceComputer Science (R0)