A Comparative Evaluation of Search Engines on Finding Specific Domain Information on the Web

  • Authors

    • Azilawati Azizan
    • Zainab Abu Bakar
    • Nurazzah Abd Rahman
    • Suraya Masrom
    • Nurkhairizan Khairuddin
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.33.23471
  • Search engine evaluation, Precision, Specific domain, Durian.
  • Abstract

    Recently search engines have provided a truly amazing search service, especially in finding general information on the Web. However, the question arises, does search engine perform the same when seeking domain specific information such as medical, geographical or agriculture information? Along with that issue, an experiment has been conducted to test the effectiveness of today’s search engines from the aspect of information searching in a specific domain. There were four search engines have been selected namely Google, Bing, Yahoo and DuckDuckGo for the experiment. While for the domain specific, we chose to test information about the popular fruit in Southeast Asia that is durian. Precision metric has been used to evaluate the retrieval effectiveness. The findings show that Google has outperformed the other three search engines. Nevertheless, the mean average precision value 0.51 given by Google is still low to be satisfied neither by the researcher nor the information seekers.

     

     

  • References

    1. [1] R. Baeza-Yates (2003), Information retrieval in the Web: Beyond current search engines. Int. J. Approx. Reason. 34 (2–3), 97–104.

      [2] R. Baeza-Yates & B. Ribeiro-Neto (1999), Modern Information Retrieval. ACM Press. Addison Wesley.

      [3] J. Singh (2013), A comparative study between keyword and semantic based search engines. Proceedings of the International Conference on Cloud, Big Data and Trust, pp. 130–134.

      [4] D. Tümer, M. A. Shah & Y. Bitirim (2009), An empirical evaluation on semantic search performance of keyword-based and semantic search engines: Google, Yahoo, Msn and Hakia. Proceedings of the Fourth Int. Conf. Internet Monit. Prot., pp. 51–55.

      [5] Y. Peng & D. He (2006), Direct comparison of commercial and academic retrieval system: An initial study. Proceedings of the International Conference on Information and Knowledge Management, pp. 1–2.

      [6] Y. Bitirim & A. K. Görür (2017), A comparative evaluation of popular search engines on finding Turkish documents for a specific time period. Teh. Vjesn. - Tech. Gaz. 24, 565–569.

      [7] J. Zhang, W. Fei & T. Le (2013), A comparative analysis of the search feature effectiveness of the major English and Chinese search engines. Online Inf. Rev. 37, 217–230.

      [8] A. K. Mariappan & V. S. Bharathi (2012), A comparative study on the effectiveness of semantic search engine over keyword search engine using TSAP measure. Proceedings of the International Conference on E-Governance and Cloud Computing Services, pp. 4–6.

      [9] N. Hariri (2013), Do natural language search engines really understand what users want? A comparative study on three natural language search engines and Google. Online Inf. Rev. 37, 287–303.

      [10] A. Azizan, Z. A. Bakar & S. A. Noah (2014), Analysis of retrieval result on ontology-based query reformulation. Proceedings of the IEEE International Conference on Computer, Communication, and Control Technology, pp. 244–248.

      [11] C. T. Lopes & C. Ribeiro (2011), Comparative evaluation of web search engines in health information retrieval. Online Inf. Rev. 35, 869–892.

      [12] F. J. Lopez-Pellicer, A. J. Florczyk, R. Béjar, P. R. Muro-Medrano, & F. Javier Zarazaga-Soria (2011), Discovering geographic web services in search engines. Online Inf. Rev. 35, 909–927.

      [13] E. Garoufallou (2012), Evaluating search engines: A comparative study between international and Greek SE by Greek librarians. Program 46, 182–198.

      [14] D. Hawking, N. Craswell, P. Bailey & K. Griffiths (2001), Measuring search engine quality. Inf. Retr. Boston. 4, 33–59.

      [15] Search Engine Watch (2018). https://searchenginewatch.com/.

      [16] Search Engine Journal (2018). https://www.searchenginejournal.com/.

      [17] Alexa.Com-TopSites (2018). https://www.alexa.com/topsites/category/Computers/Internet/Searching/Search_Engines.

      [18] B. J. Jansen, D. L. Booth & A. Spink (2009), Patterns of query reformulation during web searching. Journal of the American Society for Information Science and Technology, 60(7), 1358–1371.

      [19] M. Andago, T. P. L. Phoebe & B. A. M. Thanoun (2010), Evaluation of a semantic search engine against a keyword search engine using first 20 precision. Int. J. Adv. Sci. Arts 1(2), 55–63.

      [20] S. K. Deka & N. Lahkar (2010), Performance evaluation and comparison of the five most used search engines in retrieving web resources. Online Inf. Rev. 34, 757–771.

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  • How to Cite

    Azizan, A., Abu Bakar, Z., Abd Rahman, N., Masrom, S., & Khairuddin, N. (2018). A Comparative Evaluation of Search Engines on Finding Specific Domain Information on the Web. International Journal of Engineering & Technology, 7(4.33), 1-4. https://doi.org/10.14419/ijet.v7i4.33.23471

    Received date: 2018-12-08

    Accepted date: 2018-12-08

    Published date: 2018-12-09