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MapReduce Based Information Retrieval Algorithms for Efficient Ranking of Webpages

Author

Listed:
  • Srinivasa K.G.

    (M.S. Ramaiah Institute of Technology, India)

  • Anil Kumar Muppalla

    (M.S. Ramaiah Institute of Technology, India)

  • Bharghava Varun A.

    (M.S. Ramaiah Institute of Technology, India)

  • Amulya M.

    (M.S. Ramaiah Institute of Technology, India)

Abstract

In this paper, the authors discuss the MapReduce implementation of crawler, indexer and ranking algorithms in search engines. The proposed algorithms are used in search engines to retrieve results from the World Wide Web. A crawler and an indexer in a MapReduce environment are used to improve the speed of crawling and indexing. The proposed ranking algorithm is an iterative method that makes use of the link structure of the Web and is developed using MapReduce framework to improve the speed of convergence of ranking the WebPages. Categorization is used to retrieve and order the results according to the user choice to personalize the search. A new score is introduced in this paper that is associated with each WebPage and is calculated using user’s query and number of occurrences of the terms in the query in the document corpus. The experiments are conducted on Web graph datasets and the results are compared with the serial versions of crawler, indexer and ranking algorithms.

Suggested Citation

  • Srinivasa K.G. & Anil Kumar Muppalla & Bharghava Varun A. & Amulya M., 2011. "MapReduce Based Information Retrieval Algorithms for Efficient Ranking of Webpages," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 1(4), pages 23-37, October.
    • Handle: RePEc:igg:jirr00:v:1:y:2011:i:4:p:23-37
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