Advertisement

Search Pattern: Classifying Search Engines from a New Perspective

  • Xiao Wei
  • Yang Yang
  • Xiangfeng Luo
  • Qing Li
  • Zhiwei Tang
  • Zheng Xu
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 309)

Abstract

New types of search engines are emerging to overcome defects of traditional search engines. What the next search engine should be? It is an efficient way to classify and compare current search engines to find possible answers. This paper first defines search pattern as the combination of index structure, user profile, and interaction mechanism, which can model a search engine and help us classify search engines more essentially. Then, current search engines are classified and compared from the view of search pattern to find what the next search engine should be. Finally, a new search pattern for next generation search engine is proposed by synthesizing the advantages of different search patterns, which can help developing new search engines and may be the possible direction of the next search engine.

Keywords

search pattern index structure interaction process search engine 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hu, W.C., Chen, Y., Schmalz, M.S., et al.: An overview of world wide web search technologies. In: The Proceedings of 5th World Multi Conference on Systems, Cybernetics, Informatics, SCI 2001, Orlando, Florida, pp. 22–25 (2001)Google Scholar
  2. 2.
    Guha, R., McCool, R., Miller, E.: Semantic search. In: The Proceedings of the 12th International Conference on World Wide Web, pp. 700–709. ACM (2003)Google Scholar
  3. 3.
    Tunkelang, D.: Faceted search. Synthesis Lectures on Information Concepts, Retrieval, and Services 1(1), 1–80 (2009)CrossRefGoogle Scholar
  4. 4.
    Alisi, T., Bertini, M., D’Amico, G., et al.: Sirio: an ontology-based web search engine for videos. In: Proceedings of the 17th ACM international conference on Multimedia, pp. 967–968. ACM (2009)Google Scholar
  5. 5.
    Shehata, S., Karray, F., Kamel, M.: Enhancing search engine quality using concept-based text retrieval. In: IEEE/WIC/ACM International Conference on Web Intelligence, pp. 26–32. IEEE (2007)Google Scholar
  6. 6.
    Pilz, T., Luther, W., Fuhr, N., et al.: Rule-based search in text databases with nonstandard orthography. Literary and Linguistic Computing 21(2), 179–186 (2006)CrossRefGoogle Scholar
  7. 7.
    Levene, M.: An introduction to search engines and web navigation (2011), http://wiley.com
  8. 8.
    Morville, P., Callender, J.: Search Patterns: Design for Discovery, 1st edn. O’Reilly (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Xiao Wei
    • 1
    • 2
  • Yang Yang
    • 1
  • Xiangfeng Luo
    • 2
  • Qing Li
    • 3
  • Zhiwei Tang
    • 4
  • Zheng Xu
    • 4
  1. 1.Shanghai Institute of TechnologyShanghaiChina
  2. 2.School of Computer Engineering and ScienceShanghai UniversityShanghaiChina
  3. 3.Computer DepartmentCity University of Hong KongHong KongChina
  4. 4.The Third Research Institute of Ministry of Public SecurityHong KongChina

Personalised recommendations