Universal Mobile Information Retrieval

  • David Machado
  • Tiago Barbosa
  • Sebastião Pais
  • Bruno Martins
  • Gaël Dias
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5615)


The shift in human computer interaction from desktop computing to mobile interaction highly influences the needs for new designed interfaces. In this paper, we address the issue of searching for information on mobile devices, an area also known as Mobile Information Retrieval. In particular, we propose to summarize as much as possible the information retrieved by any search engine to allow universal access to information.


Mobile Information Retrieval Clustering of Web Page Results Automatic Summarization 


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  1. 1.
    Ferragina, P., Gulli, A.: A Personalized Search Engine Based on Web-Snippet Hierarchical Clustering. Journal of Software: Practice and Experience 38(2), 189–225 (2008)Google Scholar
  2. 2.
    Campos, R., Dias, G., Nunes, C., Nonchev, B.: Clustering of Web Page Search Results: A Full Text Based Approach. International Journal of Computer and Information Science 9(4) (2008)Google Scholar
  3. 3.
    Buyukkokten, O., Garcia-Molina, H., Paepcke, A.: Seeing the Whole in Parts: Text Summarization for Web Browsing on Handheld Devices. In: 10th International World Wide Web Conference (2000)Google Scholar
  4. 4.
    Gil, A., Dias, G.: Using Masks, Suffix Array-based Data Structures and Multidimensional Arrays to Compute Positional Ngram Statistics from Corpora. In: Workshop on Multiword Expressions of the International Conference of the Association for Computational Linguistics (2003)Google Scholar
  5. 5.
    Zamir, O., Etzioni, O.: Web Document Clustering: A Feasibility Demonstration. In: 19th Annual International SIGIR Conference (1998)Google Scholar
  6. 6.
    Fung, P., Wang, K., Ester, M.: Large Hierarchical Document Clustering using Frequent Itemsets. In: SIAM International Conference on Data Mining (2003)Google Scholar
  7. 7.
    Osinski, S., Stefanowski, J., Weiss, D.: Lingo: Search results clustering algorithm based on Singular Value Decomposition. In: Intelligent Information Systems Conference (2004)Google Scholar
  8. 8.
    Jiang, Z., Joshi, A., Krishnapuram, R., Yi, Y.: Retriever Improving Web Search Engine Results using Clustering. Journal of Managing Business with Electronic Commerce (2002)Google Scholar
  9. 9.
    Dias, G., Pais, S., Cunha, F., Costa, H., Machado, D., Barbosa, T., Martins, B.: Hierarchical Soft Clustering and Automatic Text Summarization for Accessing the Web on Mobile Devices for Visually Impaired People. In: 22nd International FLAIRS Conference (2009)Google Scholar
  10. 10.
    Dolan, W.B., Quirk, C., Brockett, C.: Unsupervised Construction of Large Paraphrase Corpora: Exploiting Massively Parallel News Sources. In: International Conference on Computational Linguistics (2004)Google Scholar
  11. 11.
    Mihalcea, R., Tarau, P.: TextRank: Bringing Order into Texts. In: Conference on Empirical Methods in Natural Language Processing (2004)Google Scholar
  12. 12.
    Vechtomova, O., Karamuftuoglu, M.: Comparison of Two Interactive Search Refinement Techniques. In: Human Language Technology Conference/North American Chapter of the Association for Computational Linguistics Annual Meeting (2004)Google Scholar
  13. 13.
    Lee, K.W., Lai, J.: Speech versus Touch: A Comparative Study of the Use of Speech and DTMF Keypad for Navigation. International Journal Human-Computer Interaction 19, 343–360 (2005)CrossRefGoogle Scholar
  14. 14.
    Parush, A.: Speech-based Interaction in a Multitask Condition: Impact of Prompt Modality. Human Factors 47, 591–597 (2005)CrossRefGoogle Scholar
  15. 15.
    Fang, X., Xu, S., Brzezinski, J., Chan, S.S.: A Study of the Feasibility and Effectiveness of Dual-modal Information Presentations. International Journal Human-Computer Interaction 20, 3–17 (2006)CrossRefGoogle Scholar
  16. 16.
    Oviatt, S.L., Lunsford, R.: Multimodal Interfaces for Cell Phones and Mobile Technology. International Journal of Speech Technology 8, 127–132 (2005)CrossRefGoogle Scholar
  17. 17.
    Fallman, D., Waterworth, J.A.: Dealing with User Experience and Affective Evaluation in HCI Design: A Repertory Grid Approach. In: Conference on Human Factors in Computing Systems (2005)Google Scholar
  18. 18.
    Frantzi, K.T., Ananiadou, S.: Retrieving Collocations by Co-occurrences and Word Order Constraint. In: 16th International Conference on Computational Linguistics (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • David Machado
    • 1
  • Tiago Barbosa
    • 1
  • Sebastião Pais
    • 1
  • Bruno Martins
    • 1
  • Gaël Dias
    • 1
  1. 1.Centre of Human Language Technology and BioinformaticsUniversity of Beira InteriorCovilhãPortugal

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