Author

  • Naveed Dastgir

    • Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology (SZABIST), Islamabad, Pakistan
    • Pakistan

  • Muhammad Naeem Ahmed Khan

    • Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology (SZABIST), Islamabad, Pakistan
    • Pakistan

Abstract

Now days, the Word Wide Web (WWW) covers most of the information channels across the world and is the cheapest resource to publish the corporate as well as individual information. The key advantage of WWW is that the published information instantly becomes available around the globe. Since the information load on the Internet is increasing day by day, therefore, it is causing serious troubles for the researchers and scientists to retrieve the targeted and relevant information from the huge bulk of data. While surfing the Internet, precious time of researchers and scientists is wasted due to browsing of the irrelevant and unnecessary material. Such an approach of information retrieval results in overlooking the important contents. In this paper, we look into the elementary components of a customized search engine in order to develop an agent-based search engine tool that may help researchers and scientists to find their desired information in an efficient manner and with minimal clicks of pointer. Through this tool, the researchers and scientists will be able to find a summarized report against their search phrase along with the search details, which will provide them a solid background to their research subject based on history available on the WWW. The important aspect of this search engine is that it retrieves the subject-specific material from the designated websites in accordance with the user-defined criteria.

Keywords

References

  • Birukov, A., Blanzieri, E. & Giorgini, P. (2005). Implicit: An Agent Based Recommendation System for Web Search. Association for Computing Machinery (ACM), Utrecht, Netherlands.
  • Cho, J. & Tomkins, A. (2007). Social Media and Search. IEEE. IEEE Computer Society.
  • Dikaiakos, D., Pallis, G., Katsaros, D., Mehra, P. & Vakali, A. (2009). Cloud Computing Distributed Internet Computing for IT and Scientific Research. IEEE INTERNET COMPUTING.
  • Ding, L., Finin, T., Joshi, A., Pan, R., Cost, R. S., Peng, Y., Reddivari, P., Doshi, V. C. & Sachs, J. (2004). Swoogle: a search and metadata engine for the semantic web. In: 13th ACM Conference on Information and Knowledge Management.
  • Durgin, K. & Sherif, S. (2008). The semantic web: a catalyst for future e-business. Emerald Group Publishing Limited , 37(1), 49-65.
  • Farooq, U., Song, Y., Carroll, J. M. & Giles, C. L. (2007). Social Bookmarking for Scholarly Digital Libraries. IEEE Computer Society, 1089-7801/072007.
  • Hepp, M. (2006). Semantic Web and Semantic Web Services Father and Son or Indivisible Twins? IEEE, IEEE INTERNET COMPUTING.
  • Heymann, P., Koutrika, G. & Garcia-Molina, H. (2007). Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges. IEEE Internet Computing , 11(6), 36-45.
  • Lond, A. (2003). The role of soft computing in intelligent machines. Physical and Engineering Sciences , 361(1809).
  • Li, Q., Lau, W. H., Leung, W. C., Li, F., Lee, V., Wah, W. & Ashman, H. (2009). Emerging Internet Technologies for E-Learning.
  • Liliana, C. & Ricardo, L. (2010). Towards a Deeper Understanding of the User’s Query Intent. Workshop on Query Representation and Understanding Geneva, Switzerland, SIGIR’2010.
  • Lohani, M. & Jeevan, V. K. J. (2007). Intelligent software agents for library applications Library Management. Emerald Group Publishing Limited , 28(3), 139-151.
  • Peristeras, V., Mentzas, G., Tarabanis, A. & Abecker, A. (2009). Transforming E-government and E- participation through IT. IEEE INTELLIGENT SYSTEMS, 1541-1672.
  • Sivashanmugatn, K., Miller, J. A., Sheth, A. P. & Verma, K. (2005). Framework for Semantic Web Process Composition. International Journal of Electronic Commerce, 9(2), 71-106.
  • Tho, Q. T., Fong, A. C. M. & Hui, S. C. (2007). A scholarly semantic web system for advanced search functions. Emerald Group Publishing Limited , 31(3), 353-364.

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How to Cite

Dastgir, N., & Khan, M. N. A. (2012). Prototype Model Agent-Based Search Engine for Researchers and Scientists. Journal of Education and Vocational Research, 3(6), 199-203. https://doi.org/10.22610/jevr.v3i6.69

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Copyright (c) 2012 Naveed Dastgir, Muhammad Naeem Ahmed Khan (Author)

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Research Paper

Published in

Vol. 3 No. 6 (2012) Teacher Development, E-Learning & Knowledge Systems View issue contents

Published

2012-06-15

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