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The Theory of Basic and Applied Research in Information Retrieval Sorting Algorithm

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Computational Intelligence and Intelligent Systems (ISICA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 874))

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Abstract

As the computer technology is advancing endlessly and the information quantity is increasing exponentially, people have raised higher and higher requirements on retrieval technique, especially with the appearance of network technique and multimedia technology. The software and hardware environment of information retrieval technique is remarkably improved, making information retrieval technique develop from traditional linear retrieval to non-linear retrieval of hypertext support, and the traditional Boolean logic retrieval model no longer dominates in the information retrieval. It is hard to predict the new changes, new technologies and new ideas induced by technological advancement, yet we can grasp the correct direction for future development of information retrieval technique via comprehensive research, comparison, and analysis.

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References

  1. Jin, F.: A primary research on information retrieval and information retrieval technology. Shanxi Libr. J. 6, 22–24+49 (2001)

    Google Scholar 

  2. Fan, W., Pathak, P., Zhou, M.: Genetic-based approaches in ranking function discovery and optimization in information retrieval—a framework. Decis. Support Syst. 47(4), 398–407 (2009)

    Article  Google Scholar 

  3. Ganzha, M., Paprzycki, M., Stadnik, J.: Combining information from multiple search engines—preliminary comparison. Inf. Sci. 180(10), 1908–1923 (2010)

    Article  Google Scholar 

  4. Zhou, H., Liu, B., Liu, J.: Research on mechanism of the information retrieval based on ontology label. Procedia Eng. 29, 4259–4266 (2012)

    Article  Google Scholar 

  5. Cao, D.N., Gardiner, K.J., Cios, K.J.: Protein annotation from protein interaction networks and Gene Ontology. J. Biomed. Inform. 44(5), 824–829 (2011)

    Article  Google Scholar 

  6. Zhai, J., Song, Y.: Semantic retrieval based on SPARQL and fuzzy ontology for electronic commerce. J. Comput. 6(10), 399–402 (2011)

    Google Scholar 

  7. Dai, W., You, Y., Wang, W., Sun, Y.: Search engine system based on ontology of technological resources. J. Softw. 6(9), 1729–1736 (2011)

    Google Scholar 

  8. Feng, J.: Current situation and prospect of information retrieval visualization. Doc. Inf. Manag. Sci. Technol. 26(03), 32–34 (2012)

    Google Scholar 

  9. Pan, Q.: Research review on information retrieval visualization. Res. Libr. Sci. (12), 7–9, 14 (2010)

    Google Scholar 

  10. Xu, Z., Feng, B., Li, W.: Grid Computing Technology. Publishing House of Electronics Industry, Beijing (2004)

    Google Scholar 

  11. Chen, F.: User-oriented one-stop retrieval. Inf. Sci. 28(12), 1828–1831 (2010)

    Google Scholar 

  12. Yao, L., Xie, T.: The status and improvement of specialized information retrieval. Libr. J. Henan 33(03), 78–79 (2013)

    Google Scholar 

  13. He, X.: Design and implementation of integrated retrieval system based on information retrieval. J. Commer. Econ. 14, 37–38 (2011)

    Google Scholar 

  14. Li, S.: A summary of personalized information retrieval technology. Inf. Stud.: Theory Appl. 32(05), 107–113 (2009)

    Google Scholar 

  15. Gao, W., Liang, L., Xia, Y.: An improved algorithm for ranking in information retrieval. J. Yunnan Nationalities Univ. (Sci. Ed.) 19(1), 52–55 (2010)

    Google Scholar 

  16. Yang, J.Y., Zhang, B., Mao, Y.: Study on information retrieval sorting algorithm in network-based manufacturing environment. Appl. Mech. Mater. 484–485, 183–186 (2014)

    Google Scholar 

  17. Zhang, X., Yu, J.: Research on model building and personalized search algorithm based on user interest model. Comput. Knowl. Technol. 12(18), 1–4 (2016)

    Google Scholar 

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Correspondence to Xinze Li .

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Li, X., Yang, J., Liu, Q. (2018). The Theory of Basic and Applied Research in Information Retrieval Sorting Algorithm. In: Li, K., Li, W., Chen, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2017. Communications in Computer and Information Science, vol 874. Springer, Singapore. https://doi.org/10.1007/978-981-13-1651-7_20

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  • DOI: https://doi.org/10.1007/978-981-13-1651-7_20

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1650-0

  • Online ISBN: 978-981-13-1651-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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