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Term Ranking and Categorization for Ad-Hoc Navigation

  • Ondrej Ševce
  • Jozef Tvarožek
  • Mária Bieliková
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6304)

Abstract

Processing information in web pages and navigation on the web can take significant amount of time for users, requiring them to employ higher cognitive processes such as generalization and categorization. Providing users with annotated entities and terms contained in the text, and adaptive navigation based on these terms could help with the comprehension and better their orientation in the information space. In this paper, we present a method for ad-hoc navigation based on automatic terms retrieval, ranking and categorization. Recognized terms and categories are used as keywords for search in available content offering information spaces. Retrieved hyperlinks can be browsed by the user, while terms and categories gained from the last analyzed page are still available. Finally, the method includes user profiling, which enables grouping of the users based on their preferred terms and categories. Our results show that ad-hoc navigation can ease access to relevant related content on the web.

Keywords

term category navigation conceptual user profile 

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References

  1. 1.
    Pazzani, M., Billsus, D.: Content-based Recommendation Systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 325–341. Springer, Heidelberg (2007)Google Scholar
  2. 2.
    Brusilovsky, P., Maybury, M.T.: From adaptive hypermedia to the adaptive web. Communications of the ACM 45(5) (2002)Google Scholar
  3. 3.
    Auer, S., Bizer, C., Lehmann, J., Kobilarov, G., Cyganiak, R., Ives, Z.: Dbpedia: A nucleus for a web of open data. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  4. 4.
    Wittek, P., Darányi, S., Tan, C.L.: Improving text classification by a sense spectrum approach to term expansion. In: Proc. of the 13th Conf. on Computational Natural Language Learning, pp. 183–191 (2009)Google Scholar
  5. 5.
    Ide, N.C., Loane, R.F., Demner-Fushman, D.: Essie: A Concept-based Search Engine for Structured Biomedical Text. American Medical Informatics Assoc. 14(3), 253–263 (2007)CrossRefGoogle Scholar
  6. 6.
    Otter, M., Johnson, H.: Lost in hyperspace: metrics and mental models. Interacting with Computers 13, 1–40 (2000)CrossRefGoogle Scholar
  7. 7.
    Milne, D., Witten, H.I.: Learning to link with Wikipedia. In: Proc. of the 17th ACM Conf. on Information and Knowledge Management, pp. 509–518 (2008)Google Scholar
  8. 8.
    Šimko, M., Bieliková, M.: Improving Search Results with Lightweight Semantic Search. In: Proc. of the Workshop on Semantic Search, SemSearch 2009 at the 18th Int. World Wide Web Conf., WWW 2009. CEUR, vol. 491, pp. 53–54 (2009)Google Scholar
  9. 9.
    Barla, M., Bieliková, M.: On Deriving Tagsonomies: Keyword Relations coming from the Crowd. In: Nguyen, N.T., Kowalczyk, R., Chen, S.-M. (eds.) ICCCI 2009. LNCS (LNAI), vol. 5796, pp. 309–320. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Iacobelli, F., Birnbaum, L., Hammond, J.K.: Tell me more, not just “more of the same”. In: Proc. of the 14th Int. Conf. on Intelligent User Interfaces, pp. 81–90 (2010)Google Scholar
  11. 11.
    Mihalcea, R., Csomai, A.: Wikify! linking documents to encyclopedic knowledge. In: CIKM 2007: Proc. of the 16th ACM Conf. on Information and Knowledge Management, pp. 233–242. ACM, New York (2007)CrossRefGoogle Scholar
  12. 12.
    Cucerzan, S.: Large-Scale Named Entity Disambiguation Based on Wikipedia Data. In: Proc. of Empirical Methods in Natural Language Processing, pp. 708–716 (2007)Google Scholar
  13. 13.
    Teevan, J., Alvarado, C., Ackerman, S.M., Karger, D.R.: The perfect search engine is not enough: a study of orienteering behavior in directed search. In: Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, pp. 415–422 (2004)Google Scholar
  14. 14.
    Fahmi, I.: C-value method for multi-word term extraction. In: Lecture for Seminar in Statistics and Methodology, Alfa-informatica, RuG (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Ondrej Ševce
    • 1
  • Jozef Tvarožek
    • 1
  • Mária Bieliková
    • 1
  1. 1.Faculty of Informatics and Information TechnologiesSlovak University of TechnologyBratislavaSlovakia

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