1 |
문성빈 (1993). 적합성피드백을 이용한 전문검색시스템의 효율성 증진을 위한 연구. 정보관리학회지, 10(2), 43-67. (Moon, Sung-Been (1993). Enhancing performance of full-text retrieval systems using relevance feedback. Journal of the Korean Society for Information Management, 10(2), 43-67.)
|
2 |
문성빈 (1997). 상이한 적합성 판정과 전문검색시스템의 평가에 관한 연구. 정보관리학회지, 14(2), 123-141. (Moon, Sung-Been (1997). Variations in relevance assessments and evaluation of the performance of full-text retrieval system. Journal of the Korean Society for Information Management, 14(2), 123-141.)
|
3 |
Amati, G., & Crestani, F. (1999). Probabilistic learning for selective dissemination of information. Information Processing and Management, 35(5), 633-654.
DOI
|
4 |
Belkin, N.J. (1984). Cognitive models and information transfer. Social Science Information Studies, 4, 111-129.
DOI
|
5 |
Belkin, N.J., Cool, C., Kelly, D., Lin, S.J., Park, S.Y., Perez-Carballo, J., & Sikora, C. (2001). Iterative exploration, design and evaluation of support for query reformulation in interactive information retrieval. Information Processing and Management, 37(3), 403-434.
DOI
|
6 |
Blair, D.C., & Maron, M.E. (1990). Full-text information retrieval: further analysis and clarification. Information Processing and Management, 26(3), 437-447.
DOI
|
7 |
Borlund, P. (2003). The concept of relevance in IR. Journal of the American Society for Information Science and Technology, 54(10), 913-925.
DOI
ScienceOn
|
8 |
Burgin, R. (1992). Variations in relevance judgements and evaluation of retrieval performance. Information Processing and Management, 28(5), 619-627.
DOI
|
9 |
Dang, E.K.F., Luk, R.W.P., Allan, J., Ho, K.S., Chan, S.C.F., Chung, K.F.L., & Lee, D.L. (2010). A new context-dependent term weight computed by boost and discount using relevance information. Journal of the American Society for Information Science and Technology, 61(12), 2514-2530.
DOI
|
10 |
Eisenberg, M.B. (1988). Measuring relevance judgments. Information Processing and Management, 24(4), 373-389.
DOI
|
11 |
Eisenberg, M.B., & Barry, C. (1988). Order effect: A study of the possible influence of presentation order on user judgments of document relevance. Journal of the American Society for Information Science, 39(1), 37-49.
|
12 |
Greisdorf, H. (2003). Relevance threshold: A multi-stage predictive model of how users evaluate information. Information Processing and Management, 39(3), 403-423.
DOI
|
13 |
Harter, S.P. (1992). Psychological relevance and information science. Journal of the American Society for Information Science, 43(9), 602-615.
DOI
|
14 |
Harter, S.P. (1996). Variation in relevance assessments and the measurement of retrieval effectiveness. Journal of the American Society for Information Science, 47(1), 37-49.
DOI
|
15 |
Lopez-Pujalte, C., Guerrero Bote, V. P., & Moya Anegon, F. (2002). A test of genetic algorithms in Relevance Feedback. Information Processing and Management, 38(6), 793-805.
DOI
|
16 |
Hjorland, B. (2010). The Foundation of the concept of relevance. Journal of the American Society for Information Science and Technology, 61(2), 217-237.
DOI
|
17 |
Huang, X., & Soergel, D. (2013). Relevance: An improved framework for explicating the notion. Journal of the American Society for Information Science and Technology, 64(1), 18-35.
DOI
ScienceOn
|
18 |
Kekalainen, J., & Jarvelin, K. (2002). Using graded relevance assessments in IR evaluation. Journal of the American Society for Information Science and Technology, 53(13), 1120-1129.
DOI
|
19 |
Lopez-Pujalte, C., Guerrero Bote, V.P., & Moya Anegon, F. (2003). Order-based fitness functions for genetic algorithms applied to relevance feedback. Journal of the American Society for Information Science and Technology, 54(2), 152-160.
DOI
|
20 |
Maglaughlin, K.L., & Sonnenwald, D.H. (2002). User perspectives on relevance criteria: A comparison among relevant, partially relevant, and not relevant. Journal of the American Society for Information Science and Technology, 53(5), 327-342.
DOI
|
21 |
Maron, M.E. (1988). Probabilistic design principles for conventional and full-text retrieval systems. Information Processing and Management, 24(3), 249-255.
DOI
|
22 |
Mizzaro, S. (1997). Relevance: The whole history. Journal of the American Society for Information Science, 48(9), 810-832.
DOI
|
23 |
Quiroga, L.M., & Mostafa, J. (2002). An experiment in building profiles in information filtering: The role of context of user relevance feedback. Information Processing and Management, 38(5), 671-694.
DOI
|
24 |
Saracevic, T. (2007b). Relevance: A review of the literature and a framework for thinking on the notion in information science. Part III: Behavior and effects of relevance. Journal of the American Society for Information Science and Technology, 58(13), 2126-2144.
DOI
|
25 |
Salton. G., & Buckley, C. (1990). Improving retrieval performance by relevance feedback. Journal of the American Society for Information Science, 41(4), 288-297.
DOI
|
26 |
Saracevic, T. (1975). Relevance: A review of and a framework for the thinking on the notion in information science. Journal of the American Society for Information Science, 26(6), 321-343.
DOI
|
27 |
Saracevic, T. (2007a). Relevance: A review of the literature and a framework for thinking on the notion in information science. Part II: Nature and manifestations of relevance. Journal of the American Society for Information Science and Technology, 58(13), 1915-1933.
DOI
|
28 |
Schamber, L. (1994). Relevance and information behavior. Annual Review of Information Science and Technology, 29(1), 3-48.
|
29 |
Schamber, L., Eisenberg, M.B., & Nilan, M.S. (1990). A re-examination of relevance: Toward a dynamic, situational, definition. Information Processing & Management, 26(6), 755-776.
DOI
|
30 |
Shaw, W.M. Jr., Wood, R.E., & Tibbo, H.R. (1991). The cystic fibrosis database: Content and research opportunities. LISR, 13, 347-366.
|
31 |
Sormunen, E. (2002). Liberal relevance criteria of TREC-counting on negligible documents? In M. Beaulieu, R. Baeza-Yates, S. Myaeng, and K. Jarvelin (Eds.), Proceedings of the SIGIR 2002 (pp. 324-330). New York: ACM.
|
32 |
Spink, A., Greisdorf, H., & Bateman, J. (1998). From highly relevant to nonrelevant: Examining different regions of relevance. Information Processing and Management, 34(5), 599-622.
DOI
|
33 |
Sormunen, E., Kekalainen, J., Koivisto, J., & Jarvelin, K. (2001). Document text characteristics affect the ranking of the most relevant documents by expanded structured queries. Journal of Documentation, 57(3), 358-376.
DOI
|
34 |
Spink, A., & Greisdorf, H. (2001). Regions and levels: Measuring and mapping users' relevance judgments. Journal of the American Society for Information Science and Technology, 52(2), 161-173.
DOI
|
35 |
Spink, A., & Losee, R.M. (1996). Feedback in information retrieval. Annual Review of Information and Science and Technology, 31, 33-78.
|
36 |
Swanson, D.R. (1986). Subjective versus objective relevance in bibliographic retrieval system. The Library Quarterly, 56, 389-398.
DOI
|
37 |
Tang, R., Shaw, W.M., & Vevea, J.L. (1999). Towards the identification of the optimal number of relevance categories. Journal of the American Society for Information Science, 50(3), 254-264.
DOI
|
38 |
Vakkari, P., & Sormunen, E. (2004). The influence of relevance levels on the effectiveness of interactive information retrieval. Journal of the American Society for Information Science and Technology, 55(11), 963-969.
DOI
|
39 |
Voorhees, E. (2001). Evaluation by highly relevant documents. In W. Croft, D. Harper, D. Kraft, and J. Hobel (Eds.), Proceedings of the SIGIR 2001 (pp. 74-82). New York: ACM.
|
40 |
Voorhees, E.M., & Harman, D.K. (Eds.) (2005). TREC: Experiment and evaluation in information retrieval. Cambridge: MIT Press.
|
41 |
Xu, Y., & Wang, D. (2008). Order effect in relevance judgment. Journal of the American Society for Information Science and Technology, 59(8), 1264-1275.
DOI
|
42 |
Xu, Y., & Chen, Z. (2006). Relevance judgment: What do information users consider beyond topicality. Journal of the American Society for Information Science and Technology, 57(7), 961-973.
DOI
|