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Concurrent Information Retrieval System (IRS) for Large Volume of Data with Multiple Pattern Multiple ( $$2^\mathrm{N}$$ 2 N ) Shaft Parallel String Matching

Author

Listed:
  • Chinta Someswara Rao

    (S.R.K.R Engineering College)

  • S. Viswanadha Raju

    (JNTUHCEJ, JNT University Hyderabad)

Abstract

The internet revolution has made the digital information easy to capture, process, store, distribute, and transmit. There is a significant development in computation and related technologies. In different walks of life, there is ever expanding usage of these technologies. As a result there is a continuous collection and storage of huge amount of data of diverse characteristics in data bases. It is indeed a challenge for the retrieval of information from this enormous amount of data. The information retrieval is an attempt to make sense of the information explanation embedded in this huge volume of data. All these aspects suggest the need of intelligent data retrieval methodologies for the retrieval of useful information. In this paper, as a concurrent information retrieval system (IRS) with multiple pattern multiple ( $$2^\mathrm{N})$$ 2 N ) shaft sequential and parallel string matching algorithms is proposed. The proposed approach concurrently retrieves the searching information from huge volume of data. Experimental results have shown that the proposed string matching algorithms reduced the search time very well in both the sequential and parallel environments.

Suggested Citation

  • Chinta Someswara Rao & S. Viswanadha Raju, 2016. "Concurrent Information Retrieval System (IRS) for Large Volume of Data with Multiple Pattern Multiple ( $$2^\mathrm{N}$$ 2 N ) Shaft Parallel String Matching," Annals of Data Science, Springer, vol. 3(2), pages 175-203, June.
    • Handle: RePEc:spr:aodasc:v:3:y:2016:i:2:d:10.1007_s40745-016-0080-1
    DOI: 10.1007/s40745-016-0080-1
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    References listed on IDEAS

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    1. Hamdi Jaber Barakat & Hisham Ali Shatnawi & Shaker Turki Ismail, 2016. "The Role of Marketing Information Systems in Reducing the Effects of the International Financial Crisis: A Study Applied on the Banks Working in the Kingdom of Saudi Arabia from Islamic Perspective," International Journal of Marketing Studies, Canadian Center of Science and Education, vol. 8(1), pages 181-190, February.
    2. Koraljka Golub & Dagobert Soergel & George Buchanan & Douglas Tudhope & Marianne Lykke & Debra Hiom, 2016. "A framework for evaluating automatic indexing or classification in the context of retrieval," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(1), pages 3-16, January.
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    Cited by:

    1. S. Viswanadha Raju & K. K. V. V. S. Reddy & Chinta Someswara Rao, 2018. "Parallel String Matching with Linear Array, Butterfly and Divide and Conquer Models," Annals of Data Science, Springer, vol. 5(2), pages 181-207, June.

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