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How Do People Make Relevance Judgment of Scientific Data? Cover

How Do People Make Relevance Judgment of Scientific Data?

Data Science Journal
Volume 19 (2020): Issue 1
By: Jianping Liu,  Jian Wang,  Guomin Zhou,  Mo Wang and  Lei Shi  
Open Access
|Mar 2020

References

  1. 1Anderson, JC and Gerbing, DW. 1988. Structural Equation Modeling in Practice: A Review of the Two-Step Approach. Psychological Bulletin, 103(3): 411–423. DOI: 10.1037/0033-2909.103.3.411
    Back to article
  2. 2Barry, CL. 1994. User-defined relevance criteria: an exploratory study. Journal of the American Society for Information Science, 45(3): 149–159. DOI: 10.1002/(SICI)1097-4571(199404)45:3<;149::AID-ASI5>3.0.CO;2-J
    Back to article
  3. 3Barry, CL and Schamber, L. 1998. Users’ criteria for relevance evaluation: A cross-situational comparison. Information Processing & Management, 34: 219–236. DOI: 10.1016/S0306-4573(97)00078-2
    Back to article
  4. 4Bateman, JA. 1998. Modeling Changes in End-user Relevance Criteria: An Information Seeking Study. Unpublished thesis (PhD), University of North Texas.
    Back to article
  5. 5Borgman, C. 2013. Scholarship in the networked world: Big data, little data, no data. Oxford: Oliver Smithies Lecture, Balliol College.
    Back to article
  6. 6Borlund, P. 2003. The concept of relevance in IR. Journal of the American Society for Information Science & Technology, 54(10): 913–925. DOI: 10.1002/asi.10286
    Back to article
  7. 7Cangur, S and Ercan, I. 2015. Comparison of Model Fit Indices Used in Structural Equation Modeling Under Multivariate Normality. Journal of Modern Applied Statistical Methods, 14(1). DOI: 10.22237/jmasm/1430453580
    Back to article
  8. 8Choi, Y and Rasmussen, EM. 2002. User’s relevance criteria in image retrieval in American history. Information Processing & Management, 38(5): 695–726. DOI: 10.1016/S0306-4573(01)00059-0
    Back to article
  9. 9Cosijn, E and Ingwersen, P. 2000. Dimensions of relevance. Information Processing & Management, 36(4): 533–550. DOI: 10.1016/S0306-4573(99)00072-2
    Back to article
  10. 10Crystal, A and Greenberg, J. 2006. Relevance criteria identified by health information users during Web searches. Journal of the American Society for Information Science and Technology, 57(10): 1368–1382. DOI: 10.1002/asi.20436
    Back to article
  11. 11da Costa Pereira, C, Dragoni, M and Pasi, G. 2010. User Evaluation of Multidimensional Relevance Assessment. IIR 2010 – Proceedings of the First Italian Information Retrieval Workshop, Padua, Italy, January 27–28, 2010.
    Back to article
  12. 12da Costa Pereira, C, Dragoni, M and Pasi, G. 2012. Multidimensional relevance: prioritized aggregation in a personalized information retrieval setting. Information Processing & Management, 48(2): 340–357. DOI: 10.1016/j.ipm.2011.07.001
    Back to article
  13. 13Downe-Wamboldt, B. 1992. Content analysis: method, applications, and issues. Issues in Health Care of Women, 13(3): 313–321. DOI: 10.1080/07399339209516006
    Back to article
  14. 14Fornell, C and Larcker, DF. 1981. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1): 39–50. DOI: 10.1177/002224378101800104
    Back to article
  15. 15Garson, GD. 2016. Partial least squares: Regression and structural equation models. Asheboro, NC: Statistical Associates Publishers.
    Back to article
  16. 16Gregory, K, Groth, P, Cousijn, H, Scharnhorst, A and Wyatt, S. 2017. Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines. arXiv: Digital Libraries.
    Back to article
  17. 17Greisdorf, HF. 2000. Relevance thresholds: A conjunctive/disjunctive model of end-user cognition as an evaluative process. Unpublished thesis (PhD), Denton, TX: University of North Texas.
    Back to article
  18. 18Hair, JF, Hult, GTM, Ringle, CM and Sarstedt, M. 2014. A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: Sage.
    Back to article
  19. 19Hair, JF, Ringle, CM and Sarstedt, M. 2011. PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory & Practice, 19(2): 139–152. DOI: 10.2753/MTP1069-6679190202
    Back to article
  20. 20Harter, SP. 1992. Psychological relevance and information science. Journal of the Association for Information Science & Technology, 43(9): 602–615. DOI: 10.1002/(SICI)1097-4571(199210)43:9<;602::AID-ASI3>3.0.CO;2-Q
    Back to article
  21. 21Henseler, J, Dijkstra, TK, Sarstedt, M, Ringle, CM, Diamantopoulos, A, Straub, D, Ketchen, D, Hair, JF, Hult, GTM and Calantone, RJ. 2014. Common Beliefs and Reality About Partial Least Squares: Comments on Rönkkö & Evermann (2013). Social Science Electronic Publishing, 17(2): 182–209. DOI: 10.1177/1094428114526928
    Back to article
  22. 22Hu, L and Bentler, PM. 1998. Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4): 424–453. DOI: 10.1037/1082-989X.3.4.424
    Back to article
  23. 23Hu, L and Bentler, PM. 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1): 1–55. DOI: 10.1080/10705519909540118
    Back to article
  24. 24Ingwersen, P and Järvelin, K. 2011. The Turn: Integration of Information Seeking and Retrieval in Context. Berlin, Germany: Springer Publishing Company, Incorporated.
    Back to article
  25. 25Inskip, C, Macfarlane, A and Rafferty, P. 2010. Creative professional users’ musical relevance criteria. Sage Publications, Inc. DOI: 10.1177/0165551510374006
    Back to article
  26. 26Laplante, A. 2010. Users’ Relevance Criteria in Music Retrieval in Everyday Life: An Exploratory Study. In: International Society for Music Information Retrieval Conference, Ismir 2010, Utrecht, Netherlands, August, 2010, 601–606.
    Back to article
  27. 27Latan, H and Ramli, NA. 2013. The Results of Partial Least Squares-Structural Equation Modelling Analyses (PLS-SEM). Social Science Electronic Publishing. DOI: 10.2139/ssrn.2364191
    Back to article
  28. 28Lew, YK and Sinkovics, RR. 2013. Crossing borders and industry sectors: behavioral governance in strategic alliances and product innovation for competitive advantage. Long Range Planning, 46(s1–2): 13–38. DOI: 10.1016/j.lrp.2012.09.006
    Back to article
  29. 29Liu, JP, Wang, J and Zhou, GM. 2019. Understanding relevance judgment in the view of perceived value. Library & Information Science Research, 41(4). DOI: 10.1016/j.lisr.2019.100982
    Back to article
  30. 30Markkula, M and Sormunen, E. 2000. End-User Searching Challenges Indexing Practices in the Digital Newspaper Photo Archive. Information Retrieval, 1(4): 259–285. DOI: 10.1023/A:1009995816485
    Back to article
  31. 31Nevitt, J and Hancock, GR. 2001. Performance of Bootstrapping Approaches to Model Test Statistics and Parameter Standard Error Estimation in Structural Equation Modeling. Structural Equation Modeling A Multidisciplinary Journal, 8(3): 353–377. DOI: 10.1207/S15328007SEM0803_2
    Back to article
  32. 32Perreault, WD and Leigh, LE. 1989. Reliability of nominal data based on qualitative judgments. Journal of Marketing Research, 26(2): 135–148. DOI: 10.1177/002224378902600201
    Back to article
  33. 33Ralf, W and Siegfried, PG. 2015. The impact of dynamic capabilities on operational marketing and technological capabilities: investigating the role of environmental turbulence. Journal of the Academy of Marketing Science, 43(2): 181–199. DOI: 10.1007/s11747-014-0380-y
    Back to article
  34. 34Ringle, CM, Wende, S and Becker, JM. 2015. Smart PLS 3. Bönningstedt: SmartPLS. Retrieved from http://www.smartpls.com.
    Back to article
  35. 35Sanderson, M and Croft, WB. 2012. The History of Information Retrieval Research. Proceedings of the IEEE, 100(6): 1444–1451. DOI: 10.1109/JPROC.2012.2189916
    Back to article
  36. 36Saracevic, T. 1975. RELEVANCE: A Review of and a Framework for the Thinking on the Notion in Information Science. Journal of the Association for Information Science & Technology, 26: 1915–1933. DOI: 10.1002/asi.20682
    Back to article
  37. 37Saracevic, T. 2016. The Notion of Relevance in Information Science: Everybody knows what relevance is. But, what is it really? Synthesis Lectures on Information Concepts Retrieval & Services, 8(3): 1–109. DOI: 10.2200/S00723ED1V01Y201607ICR050
    Back to article
  38. 38Savolainen, R and Kari, J. 2013. User-defined relevance criteria in web searching. Journal of Documentation, 62(6): 685–707. DOI: 10.1108/00220410610714921
    Back to article
  39. 39Schamber, L. 1990. Users’ Criteria for Evaluation in a Multimedia Environment. Proceedings of the American Society for Information Science & Technology, 28(6): 126–133.
    Back to article
  40. 40Taylor, RS. 1968. Question-negotiation and information seeking in libraries. College & Research Libraries, 29. DOI: 10.5860/crl_29_03_178
    Back to article
  41. 41Tombros, A, Ruthven, I and Jose, JM. 2003. Searchers’ criteria for assessing web pages. In: International ACM SIGIR Conference on Research and Development in Informaion Retrieval, Toronto, Canada, 28 July–01 Aug 2003. 385–386.
    Back to article
  42. 42Wang, PL and Soergel, D. 1998. A cognitive model of document use during a research project. Study I. Document selection. Journal of the American Society for Information Science, 49(2): 115–133. DOI: 10.1002/(SICI)1097-4571(199802)49:2<;115::AID-ASI3>3.0.CO;2-T
    Back to article
  43. 43Xu, Y and Chen, Z. 2006. Relevance judgment: What do information users consider beyond topicality? Journal of the American Society for Information Science & Technology, 57(7): 961–973. DOI: 10.1002/asi.20361
    Back to article
DOI: https://doi.org/10.5334/dsj-2020-009 | Journal eISSN: 1683-1470
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Language: English
Submitted on: May 9, 2019
Accepted on: Jan 15, 2020
Published on: Mar 9, 2020
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
scientific data,
data retrieval,
user relevance,
relevance criteria

© 2020 Jianping Liu, Jian Wang, Guomin Zhou, Mo Wang, Lei Shi, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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