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A Novel Ranking Model for a Large-Scale Scientific Publication

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Abstract

With a large number of scientific literature, it has been difficult to search for a set of relevant articles and to rank them. In this work, we propose a generalized network analysis approach (called N-star ranking model) for sorting them based on . The ranking of the result is considered in the mutual relationships between another classes: keyword, publication, citation. From the model, we propose two ranks for this problem: the Universal-Publication rank - (UP rank) and Topic-Publication rank (TP rank). We also study two simple ranks based on citation counting (RCC rank) and content matching (RCM rank). We propose the metrics for ranking comparison and analysis on two criteria value and order. We have conducted the experimentations for confirming the predictions and studying the features of the ranks. The results show that the proposed ranks are very impressive for the given problem since they consider the query/topic, the content of publication and the citations in the ranking model.

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Notes

  1. Several famous keyword based scientific search engine are Google Scholar (http://scholar.google.com), Microsoft Academic Search(http://academic.research.microsoft.com/), ArnetMiner (http://arnetminer.org/), etc

  2. http://academic.research.microsoft.com/ - Accessed on December 2013

  3. http://core.edu.au/

  4. NS is the short of N-star ranking model

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Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF-2014R1A2A2A05007154). Also, this work was supported by the MSIP (Ministry of Science, ICT&Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (NIPA-2014-H0301-14-1044) supervised by the NIPA (National ICT Industry Promotion Agency).

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Authors and Affiliations

  1. Department of Computer Engineering, Chung-Ang University, Seoul, South Korea

    Bong-Soo Sohn

  2. Department of Computer Science and Engineering, Chung-Ang University, Seoul, South Korea

    Jai E. Jung

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  1. Bong-Soo Sohn
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  2. Jai E. Jung
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Correspondence to Jai E. Jung.

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Sohn, BS., Jung, J.E. A Novel Ranking Model for a Large-Scale Scientific Publication. Mobile Netw Appl 20, 508–520 (2015). https://doi.org/10.1007/s11036-014-0539-2

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