Skip to main content
SpringerLink
Log in
Book cover

Asian Conference on Intelligent Information and Database Systems

ACIIDS 2016: Intelligent Information and Database Systems pp 202–211Cite as

A Method for Determining Representative of Ontology-Based User Profile in Personalized Document Retrieval Systems

  • Conference paper

  • 2306 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9621))

Abstract

Information overload is one of the most important problems in context of personalized document retrieval systems. In this paper we propose to use ontology-based user profile. Ontological structures are appropriate to represent relations between concepts in user profile. We present a method for determining representative profile of users’ group. Two users are in the same group when their interests (profiles) are similar. If a new user is classify to a group, a system can recommend him a representative profile to avoid ,,cold-start problem”. Results obtained in experimental evaluation are promising. Method presented in this paper is a crucial part of developed personalized document retrieval system.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

References

  1. Cantador, I., Bellogin, A., Castells, P.: A multilayer ontology-based hybrid recommendation model. J. AI Commun. - Recomm. Syst. 21(2–3), 203–210 (2008)

    MathSciNet  MATH  Google Scholar 

  2. Cantador, I., Szomszor, M., Alani, H., Fernandez, M., Castells, P.: Enriching ontological user profiles with tagging history for multi-domain recommendations. In: Proceedings of 1st International Workshop on Collective Semantics: Collective Intelligence & the Semantic Web (2008)

    Google Scholar 

  3. Cruz, I.F., Xiao, H.: The role of ontologies in data integration. J. Eng. Intell. Syst. 13(5), 245–252 (2005)

    Google Scholar 

  4. Etaati, L., Sundaram, D.: Adaptive tourist recommendation system: conceptual frameworks and implementation. Vietnam J. Comput. Sci. 2, 95–107 (2015). doi:10.1007/s40595-014-0034-5

    Article  Google Scholar 

  5. Limbu, D.K., Connor, A.M., MacDonell, S.G.: A framework for contextual information retrieval from the WWW. arXiv preprint (2014). arXiv:1407.6100

  6. Luna, V., Quintero, R., Torres, M., Moreno-Ibarra, M., Guzman, G., Escamilla, I.: An ontology-based approach for representing the interaction process between user profile and its context for collaborative learning environments. Comput. Hum. Behav. 51, 1387–1394 (2015)

    Article  Google Scholar 

  7. Maleszka, M., Mianowska, B., Nguyen, N.T.: A method for collaborative recommendation using knowledge integration tools and hierarchical structure of user profiles. Knowl.-Based Syst. 47, 1–13 (2013)

    Article  Google Scholar 

  8. Maleszka, B.: A method for profile clustering using ontology alignment in personalized document retrieval systems. In: Núñez, M., et al. (eds.) ICCCI 2015. LNCS, vol. 9329, pp. 410–420. Springer, Heidelberg (2015). doi:10.1007/978-3-319-24069-5_39

    Chapter  Google Scholar 

  9. Mianowska, B., Nguyen, N.T.: Tuning user profiles based on analyzing dynamic preference in document retrieval systems. Multimedia Tools Appl. 65, 93–118 (2012). doi:10.1007/s11042-012-1145-6

    Article  Google Scholar 

  10. Montaner, M., Lopez, B., Rosa, J.: A taxonomy of recommender agents on the internet. Artif. Intell. Rev. 19, 258–330 (2003)

    Article  Google Scholar 

  11. Noy, N.F., Musen, M.A.: An algorithm for merging and aligning ontologies: automation and tool support. In: Proceedings of the Workshop on Ontology Management at the Sixteenth National Conference on Artificial Intelligence (1999)

    Google Scholar 

  12. Noy, N.F.: Semantic integration: a survey of ontology-based approaches. SIGMOD Rec. 33, 65–70 (2004)

    Article  Google Scholar 

  13. Pietranik, M., Nguyen, N.T.: A multi-attribute based framework for ontology aligning. Neurocomput. 146, 276–290 (2014)

    Article  Google Scholar 

  14. Pinto, H.S., Martns, J.P.: Ontology integration: how to perform the process. In: Proceedings of the IJCAI-01 Workshop on Ontologies and Information Sharing (2001)

    Google Scholar 

  15. Pinto, H.S., Gomez-Perez, A., Martins, J.P.: Some issues on ontology integration. In: Proceedings of the IJCAI-99 workshop on Ontologies and Problem-Solving Methods (1999)

    Google Scholar 

  16. Zhu, Y., Xiong, L., Verdery, C.: Anonymizing user profiles for personalized web search. In: Proceedings of the 19th International Conference on World Wide Web, WWW 2010 (2010)

    Google Scholar 

Download references

Acknowledgments

This research was partially supported by Polish Ministry of Science and Higher Education.

Author information

Authors and Affiliations

  1. Faculty of Computer Science and Management, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Bernadetta Maleszka

Authors
  1. Bernadetta Maleszka
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bernadetta Maleszka .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

  3. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Maleszka, B. (2016). A Method for Determining Representative of Ontology-Based User Profile in Personalized Document Retrieval Systems. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-49381-6_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49380-9

  • Online ISBN: 978-3-662-49381-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation