Title page for 89443008


[Back to Results | New Search]

Student Number 89443008
Author Gen-Ming Guo(³¢«Ø©ú)
Author's Email Address sambuela@gmail.com
Statistics This thesis had been viewed 2151 times. Download 1077 times.
Department Information Management
Year 2004
Semester 2
Degree Ph.D.
Type of Document Doctoral Dissertation
Language English
Title A Computer-Aided Bibliometric Systems for the Core Journal and Article Ranking of Multidisciplinary Departments and Subjects
Date of Defense 2005-06-01
Page Count 117
Keyword
  • Article Ranking
  • Bibliometry
  • Citation Analysis
  • Computer-Aided Bibliometric Systems
  • Journal Ranking
  • Abstract Due to the tremendous increase and variation in serial publications, the impact of every journal to multidisciplinary departments or subjects is becoming more changeable. While scholars are finding it impossible to update their departmental/subject core journal/article ranking lists regularly and accurately. The evaluation of serial journals/papers for ranking departmental/subject core journal/paper lists becomes a very challenging task for departmental faculties and librarians. Therefore, a CABS (Computer-Aided Bibliometric Systems) was proposed. There are five subsystems in the CABS, which are the DJCABS (Departmental Journal CABS), SJCABS (Subject Journal CABS), DACABS (Departmental Article CABS), BJCABS (Biomedical Journal CABS) and SACABS (Subject Article CABS).
    In the DJCABS, two methods (JCDF and LibJF) were proposed. One citation pattern was found and the ratio of TP-to-NoJournal was always around 0.07 among the 10 journals and 6 departments. After comparing with four methods via overlapping rate, standard deviation distances and correlation factor, the two proposed methods were shown to outperform the questionnaire and library subscription method.
    For the SJCABS, Subtract Self-Journal Cited Factor (SJCDF) was proposed. The TA-Ratio was always around 0.07 for 7 subjects and the top 10 journals. Two types of ratios exist in the journal citation ratio distribution. Type I is ¡§1:1.5n:1.8n¡¨ and Type II is ¡§ ¡¨. These ratios can be helpful when deciding the core journal area. After comparing with three other methods (SIM, DIF and WSM) via the Correlation factor, SJCDF was shown to be at an acceptance level. The journal¡¦s self citation problem was shown to be a serious bias in this study. SJCDF removes this noise which others ignore.
    As for the DACABS, four indicators (RCC, TCC, PI and CH) were proposed. These four methods were designed to satisfy different audiences¡¦ requirements. All TP were located at the 4th segment for all departments/journals by the TCC method. Through the RCC method, TPs from different departments/journals were classified into two types. The TP site of Type I was 0.07 and Type II was 0.14. After comparing these four methods via the Correlation factor, both RCC and TCC obtained more than 0.5 and 0.9 Correlation factors with their own extended methods.
    For the SACABS, four indicators (SRCC, STCC, SPI and SCH) were proposed. All TPs were located at the 3rd segment for all subjects by the STCC. The TC Ratios are all about 0.2. The TP Angles are all about 70 degrees. Using the SRCC, all TPs from different subjects were all located at the 1st segment. Both TC Ratios and TP Angles are close to the experimental results from STCC indicator. The patterns of TC Ratios and TP Angles are 0.2 and 70. In addition, both SRCC and STCC can get more than 0.7 and 0.9 correlation factors with SRPI/SRCH and STPI/STCH. SRCC/SRPI/SRCH has more than 0.72 correlation factors with ¡¥Google Scholar¡¦.
    Table of Content Table of Contents
    AbstractI
    List of Illustrative MaterialsV
    List of TablesVIII
    Chapter 1 Introduction1
    1.1 Background and Motivation1
    1.2 Purposes and Contributions1
    1.3 Methods and Results2
    1.4 Organization of Contents5
    Chapter 2 Related Works for Computer-Aided Bibliometric Systems6
    2.1 Departmental Core Journal Ranking6
    2.2 Subject Core Journal Ranking6
    2.3 Departmental Core Article Ranking7
    2.4 Biomedical Journal Bibliometry7
    2.5 Subject Core Article Ranking8
    Chapter 3 Materials and Methods9
    3.1 Materials of Sources of DataBase9
    3.1.1 ISI JCR and WOS DataBase9
    3.1.2 NCU Library Weblog and Web Proxy Cache (Worthless)10
    3.1.3 NIH PubMed DataBase11
    3.2 Methods of Computer-Aided Bibliometric Systems12
    3.2.1 System Design for Different CABS12
     3.2.1.1 DJCABS13
     3.2.1.2 SJCABS15
     3.2.1.3 DACABS16
     3.2.1.4 BJCABS17
     3.2.1.5 SACABS26
    3.2.2 Ranking Methods for Different CABS27
     3.2.2.1 Departmental Core Journal Ranking Method27
     3.2.2.2 Subject Core Journal Ranking Method29
     3.2.2.3 Departmental and Subject Core Article Ranking Method31
    3.2.3 Relevant Analysis Methods33
     3.2.3.1 Directed Maximum Spanning Tree33
    3.2.4 System Demo for Computer-Aided Bibliometric Systems33
     3.2.4.1 DJCABS33
     3.2.4.2 SJCABS35
     3.2.4.3 DACABS36
     3.2.4.4 BJCABS37
     3.2.4.5 SACABS41
    Chapter 4 Results and Discussions42
    4.1 Departmental Core Journal Ranking43
    4.1.1 Individual and Accumulated Journal Citation Analysis43
    4.1.2 Journal Overlapping Analysis47
    4.1.3 Journal Cited/Citing Analysis49
    4.1.4 Departmental Core Journal Analysis51
    4.2 Subject Core Journal Ranking61
    4.2.1 Journal Citation Analysis61
    4.2.2 Journal Cited/Citing Analysis64
    4.2.3 DMST Analysis66
    4.2.4 Comparison of Different Methods67
    4.3 Departmental Core Article Ranking72
    4.3.1 Author Self-Citations72
    4.3.2 The Turning Point Pattern73
    4.3.3 The Myths75
    4.3.4 Comparison of Different Methods78
     4.3.4.1 Citation Network Analysis78
     4.3.4.2 Strength and Weakness78
     4.3.4.3 Correlation and Distance80
    4.4 Biomedical Journal Literature Analysis82
    4.4.1 Subject and Time Series Analysis82
    4.4.2 Researcher and Unit Analysis84
    4.4.3 Country and Continent Analysis85
    4.4.4 Journal Analysis86
    4.5 Subject Core Article Ranking88
    4.5.1 Author Self-Citations88
    4.5.2 The Turning Point Pattern88
    4.5.3 The Myths90
    4.5.4 Comparing of Different Methods92
    4.5.5 Graphical Data Presentation95
    Chapter 5 Conclusion and Future Work100
    5.1 Conclusion100
    5.2 Future Work101
    Bibliography102
    Appendix105
    Reference Bibliography
    Abdel-Hamid, T. K., Sengupta, K. and Swett, C. (1999), The Impact of Goals on Software Project Management: An Experimental Investigation. MIS Quarterly, 23:4, 531-555.
    Barbara, S. Shearer and Suzanne, P. Nagy (2003), Developing an Academic Medical Library Core Journal Collection in the Post-print Era: The Florida State University College of Medicine Medical Library Experience, Journal Medical Library Association, 91:3, 292-302.
    Bradford, S. C. (1934), Sources of Information on Specific Subjects, Engineering, 137, 85-86.
    Bradford, S. C. (1948), London: Crosby Lockwood & Sons, Documentation.
    Brin, S. and Page, L. (1998), The Anatomy of a Large-Scale Hypertextual Web Search Engine, WWW7/Computer Network, 30:1-7, 107-117.
    Brookes, B. C. (1968), The Derivation and Application of the Bradford-Zipf Distribution, Journal of Documentation, 24, 247-265.
    Bhargava, H. K., Sridhar, S. and Herrick, C. (1999). Beyond Spreadsheets: Tools for Building Decision Support Systems, Computer, 32:3, 31-39.
    Chang, S. S. (2001), Research Method, Taiwan, Tsang-Hai Press, 561-607.
    Christine, L. B. and Jonathan, F. (2002), Scholarly Communication and Bibliometrics, Annual Review of Information Science and Technology, 36, 1-45
    Chun, C., Ashok, K., Jaideep, G., Motwani, R. and Manu, M. (1999), A Citation Analysis of the Technology Innovation Management Journals, IEEE Transactions on Engineering Management, 46:1, 4-13.
    CiteSeer Search Engine (2005), 4/13-last access, Available: citeseer.ist.psu.edu.
    Fu, Ya-hsiu (2002), Scientific Collaboration and Coauthors in Life Science Journal Articles, Journal of library and information studies, 17, 71-80.
    Hardgrave, B. C. and Walstrom, K. A. (1997), Forum for MIS Scholars, Communications of ACM, 40:11, 119-124.
    Hardgrave, B. C. and Walstrom, K. A. (2001), Forums for Information Systems Scholars: III¡¨, Information and Management, 39, 117-124.
    HighWire Database (2005), 4/5-last access, Available: highwire.stanford.edu.
    Hirst, G. and Talent, N. (1977), Computer Science Journals: An Iterated Citation Analysis, IEEE Transactions on Professional Communication, 20:4, 233-238.
    Hirst, G. (1978), Discipline Impact Factors: A Method for Determining Core Lists, Journal of the American Society for Information Science, 29, 171-172.
    Holsapple, C. W., Johnson, L. E., Manakyan, H. and Tanner, J. (1993), A Citation Analysis of Business Computing Research Journals, Information Management, 25:5, 231-244.
    Huang, H. H. and Hsu, Jack (2005), An Evaluation of Publication Productivity in Information Systems: 1999 to 2003, Communications of the Association for Information Systems, 15, 555-564.
    Hwang, S. Y., Lia, S. G., Lian, D. P. and Shung, P. G. (2001), A Survey of Journal Publications of Information Management Department in Taiwan, Journal of Information Management, 9:1, 217-239.
    ISI Corp. (2005), 1/14-last access, ISI Web of Knowledge. Available: www.isinet.com.
    Janice, S. L. and John, D. M. (2002), Defining the Undergraduate Core Journal Collection, The Serials Librarian, 43:1, 45-59.
    Jeffrey, D. K., Kristin, H. G. and Cynthia, D. (1998), A Method for Building Core Journal Lists in Interdisciplinary Subject Areas, Journal of Document, 54:4, 477-488.
    Jiawei, H. and Micheline, K. (2001), Data Mining: Concepts and Techniques, Morgan Kaufmann publishers.
    Junping, Q. (2002), The Course, Status quo and Trend of Bibliometrics in China, Journal of Information, Communication and Library Science, 9:1, 1-11.
    King, J. (1987), A Review of Bibliometric and Other Science Indicators and Their Role in Research Evaluation, Journal of Information Science, 13:5, 261-276.
    Kobulnicky, P. J. (1977), Physics libraries and literature, Encyclopedia of Library and Information Sciences, 22, 214-248.
    Leslie, K. W. (1996), Exciting Potential of Scholarly Electronic Journals, CAUT Bulletin, 43:7, 9-15.
    Lian, D. P. (2003), Decision Support Systems and Business Intelligence, Best-Wise press.
    Liker, J. (1995), Results of Survey of Management Journals for TIM Research, TIM Newslett., 7:2, 5-8.
    Luukkonen, T. (1990), Bibliometrics and Evaluation of Research Performance, Annals of Medicine, 22:3, 145-150.
    MathWorld (2005), 4/19-last update, Correlation Coefficient, Available: mathworld.wolfram.com/CorrelationCoefficient.html.
    Mela, G. S. (2003), Radiological Research in Europe: A Bibliometric Study, European Radiology, 13:4, 657-662.
    Michael, J. Berry and Gordon, Linoff (1997), Data Mining Techniques: for Marketing, Sales, and Customer Support, John Wiley & Sons, Inc. press.
    Microarray Gene Expression Data Society (MGED) (2004), 12/17-last access, Available: www.mged.org.
    Mylonopoulos, N. A. and Theoharakis, V. (2001), Global Perceptions of IS Journals, Communications of ACM, 44:9, 29-33.
    NCU Library (2004), 2/18-last access, Journal Search Engine of NCU Library. Available: dns1.lib.ncu.edu.tw/~collin/carry/title.php.
    PubMed Database (2005), 1/6-last access, Available: www.ncbi.nih.org/pubmed.
    Robert, V. Hogg, Allen, C. and Joseph, W. McKean (2004), Introduction to Mathematical Statistics 6th Edition, Prentice Hall Press.
    Scholar Search Engine (2005), 1/7-last access, Available: scholar.google.com.
    Shiue, Y. C., Chang, R. I. and Guo, G. M. (2004), A Computer-Aided Bibliometrics System for Journal Citation Analysis and Departmental Core Journal Ranking List Generation, Journal of Educational Media & Library Sciences, 42:2, 199-220.
    Sircar, S., Nerur, S. P. and Mahapatra, R. (2001), Revolution or Evolution? A Comparison of Object-Oriented and Structured Systems Development Methods, MIS Quarterly, 25:4, 457-471.
    Snyder, H. and Bonzi, S. (1998), Patterns of Self-Citation across disciplines, Journal of Information Science, 24:6, 431-435.
    Squid Cache Organization (2004), 4/10-last access, Squid Web Proxy Cache, Available: www.squid-cache.org.
    Stanford Microarray Database (2003), 10/12-last access, Available: genome-www5.stanford.edu.
    Steven, N., Cheehung, C. and Vijay, R. (2002), Visualization of Document Co-citation Counts, Proceedings of the Sixth International Conference on Information Visualization, 691-696.
    Tanebaum, A. S. (2000), Computer Networks, Prentice Hall press, 1-46.
    Thomson Corp. (2005), 1/3-last access, ISI Web of Knowledge and Journal Citation Report, Available: www.isinet.com.
    U.S. News Corp. (2004), 3/25-last access, American Colleges Ranking, Available: www.usnews.com/usnews/rankguide/rghome.htm.
    Yun, Y. J. (1980), Business Statistics, Taiwan, Sanmin Press, 675-699
    Zhiren, Z. (2002), On the Characteristic Chinese Database-Chinese Social Science Citation Index, Journal of Information, Communication and Library Science, 9:1, 57-61.
    Zipf, G. K. (1949), Human Behavior and the Principle of Least Efforts: An Introduction to Human Ecology, Addison Wesley.
    Advisor
  • Y. C. Shiue(Á§¸q¸Û)
  • Files
  • 89443008.pdf
  • approve immediately
    Date of Submission 2005-06-14

    [Back to Results | New Search]


    Browse | Search All Available ETDs

    If you have dissertation-related questions, please contact with the NCU library extension service section.
    Our service phone is (03)422-7151 Ext. 57407,E-mail is also welcomed.