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http://dx.doi.org/10.3743/KOSIM.2012.29.4.273

An Approach Toward Image Access Points based on Image Needs in Context of Everyday Life  

Chung, EunKyung (이화여자대학교 사회과학대학 문헌정보학과)
Chung, SunYoung (이화여자대학교 일반대학원)
Publication Information
Journal of the Korean Society for information Management / v.29, no.4, 2012 , pp. 273-294 More about this Journal
Abstract
Images have been substantially searched and used due to not only the advanced internet and digital technologies but the characteristics of a younger generation. The purpose of this study aims to discuss the ways on expanding the access points to images by analyzing the needs of users in context of everyday life. In order to achieve the purpose of this study, 105 questions of image seeking in NAVER, which is one of social Q&A services in Korea, were analyzed. For the analysis, a two-dimensional framework with image uses and image attributes were utilized. The findings of this study demonstrate that considerable use purposes on data oriented pole, such as information processing, information dissemination and learning are identified. On the other hand, image attributes from the needs of image show that non-visual aspects including contextual attributes are recognized substantially in addition to the traditional semantic attributes.
Keywords
image; information needs; everyday life; information behavior; searching model; indexing; access point; social Q&A;
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Times Cited By KSCI : 3  (Citation Analysis)
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1 이지연 (2002). 이용자 관점에서 본 이미지 색인의 객관성에 대한 연구. 정보관리학회지, 19(3), 123-144.(Lee, Jee-Yeon (2002). An investigation of the objectiveness of image indexing from users' perspectives. Journal of the Korean Society for information Management, 19(3), 123-144.)   과학기술학회마을   DOI   ScienceOn
2 Beaudoin, J. E., & Brady, J. E. (2011). Finding visual information: A study of image resources used by archaeologists, architects, art historians, and artists. Art Documentation, 30(2), 24-36.
3 Chen, H. (2001). An analysis of image queries in the field of art history. Journal of the American Society for Information Science and Technology, 52(3), 260-273.   DOI
4 Chen, H., Kochtanek, T., Sean Burns, C., & Shaw, R. (2010). Analyzing users' retrieval behaviours and image queries of a photojournalism image databases. The Canadian Journal of Information and Library Science, 34(3), 249-270. http://dx.doi.org/10.1353/ils.2010.0003   DOI
5 Choi, Y. (2010). Effects of contextual factors on image searching. Journal of the American Society for Information Science and Technology, 61(10), 2011-2028. http://dx.doi.org/10.1002/asi.21386   DOI   ScienceOn
6 Choi, Y., and Rasmussen, E. (2003). Searching for images: The analysis of users' queries for image retrieval in American history. Journal of the American Society for Information Science and Technology, 54(6), 498-511. http://dx.doi.org/10.1002/asi.10237   DOI   ScienceOn
7 Chung, E. (2010). A preliminary examination on the multimedia information needs and web searches of college students in Korea. Journal of the Korean Society for Library and Information Science, 44(4), 95-114. http://dx.doi.org/10.4275/KSLIS.2010.44.4.095   과학기술학회마을   DOI   ScienceOn
8 Chung, E., & Yoon, J. (2011). Image needs in the context of image use: An exploratory study. Journal of Information Science, 37(2), 163-177. http://dx.doi.org/10.1177/0165551511400951   DOI   ScienceOn
9 Conniss, L. R., Ashford, A. J., & Graham, M. E. (2000). Information seeking behavior: Visor I final report. Library and Information Commission Research Report 95. Institute for Image Data Research, Newcastle upon Tyne.
10 Cunningham, S. J., Bainbridge, D., & Masoodian, M. (2004). How people describe their image information needs: A grounded theory analysis of visual arts queries. Proceedings of the Joint Conference on Digital Libraries, 47-48
11 Cunningham, S. J., & Masoodian, M. (2006). Looking for a picture: An analysis of everyday image information searching. Proceedings of the 6th ACM/IEEE-CS Joint Conference On Digital Libraries. 198-199.
12 Eakins, J., Briggs, P., & Burford, B. (2004). Image retrieval interfaces: A user perspective. Lecture Notes in Computer Science, 3115, 628-637.
13 Fidel, R. (1997). The image retrieval task: Implications for the design and evaluation of image databases. The New Review Hypermedia and Multimedia, 3, 181-200.   DOI   ScienceOn
14 Enser, P. G. B., & McGregor, C. (1992). Analysis of visual information retrieval queries: British Library R&D Report No. 6104.
15 Enser, P. G. B. (1995). Pictorial information retrieval. Journal of Documentation, 51(2), 126-170.   DOI   ScienceOn
16 Enser, P. G. B., Sandom, C. J., Hare, J. S., & Lewis, P. H. (2007). Facing the reality of semantic image retrieval. Journal of Documentation, 63(4), 465-481. http://dx.doi.org/10.1108/00220410710758977   DOI   ScienceOn
17 Fukumoto, T. (2006). An analysis of image retrieval behavior for metadata type image database. Information Processing and Management, 42, 723-728. http://dx.doi.org/10.1016/j.ipm.2005.01.008   DOI   ScienceOn
18 Goodrum, A., & Spink, A. (2001) Image searching on the Excite Web search engine. Information Processing and Management, 37, 295-311. http://dx.doi.org/10.1016/S0306-4573(00)00033-9   DOI   ScienceOn
19 Hasting, S. K. (1995). Query categories in a study of intellectual access to digitized art images. Proceedings of the 58th Annual Meeting of the American Society for Information Science, 3-8.
20 Hollink, L., Schreiber, A. Th., Wielinga, B. J., & Worring, M. (2004). Classification of user image descriptions. International Journal of Human-Computer Studies, 61, 601-626. http://dx.doi.org/10.1016/j.ijhcs.2004.03.002   DOI   ScienceOn
21 Jamies, A. (2006). Human factors in automatic image retrieval system design and evaluation. Proceedings of IS&T/SPIE Internet Imaging VII, 101-109. http://dx.doi.org/10.1117/12.660255   DOI
22 Jorgensen, C. (1998). Attributes of images in describing tasks. Information Processing & Management, 34(2/3), 161-174. http://dx.doi.org/10.1016/S0306-4573(97)00077-0   DOI   ScienceOn
23 Jamies, A. & Chang, S. (2000). A conceptual framework for indexing visual information at multiple levels. IS&T/SPIE Internet Imaging, 3964. 2-15.
24 Jensen, B. J. (2008). Searching for digital images on the web. Journal of Documentation, 64(1), 81-101. http://dx.doi.org/10.1108/00220410810844169   DOI   ScienceOn
25 Jean, B. St., Rieh, S. Y., Kim, Y. -M., & Yang, J. Y. (2012). An analysis of the information behaviors, goals, and intentions of frequent Internet users: Findings from online activity diaries. First Monday, 17(2). Retrieved from http://www.uic.edu/htbin/cgiwrap/bin/ojs/index.php/fm/article/viewArticle/3870/3143
26 Jorgensen, C. (2001). A conceptual framework and empirical research for classifying visual descriptors. Journal of the American Society for Information Science and Technology, 52(11), 938-947. http://dx.doi.org/10.1002/asi.1161   DOI   ScienceOn
27 Krause, M. C. (1998). Intellectual problems of indexing picture collections. Audiovisual Librarian, 14(2), 73-81.
28 Markkula, M., & Sormunen, E. (2000). End-user searching challenges indexing practices in the digital newspaper photo archive. Information Retrieval, 1(4), 250-285.
29 McCay-Peet, L., & Toms, E. (2009). Image use within the work task model: Images as information and illustration. Journal of the American Society for Information Science and Technology, 60(12), 2416-2429. http://dx.doi.org/10.1002/asi.21202   DOI   ScienceOn
30 Oranger, S. (1995). The newspaper image database: Empirical supported analysis of users' typology and word association clusters. Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '95), 212-218.
31 Seo, Eun-Gyoung, & Lee, Won-Kyung (2008). The access-enhanced search interface design for Korean paintings. Journal of the Korean Society for Information Management, 25(2), 25-48. http://dx.doi.org/10.3743/KOSIM.2008.25.2.025   과학기술학회마을   DOI   ScienceOn
32 Panofsky, E. (1962). Studies in iconology: Humanistic themes in the art of renaissance. New York: Harper & Rowe.
33 Pu, H. (2005). A comparative analysis of web image and textual queries. Online Information Review, 29(5), 457-467. http://dx.doi.org/10.1108/14684520510628864   DOI   ScienceOn
34 Schlak, T. (2010). Image retrieval as information seeking behavior? Self-categorizations of user motivations to retrieve images. Unpublished doctoral dissertatioin, University of Pittsburgh, PA, USA.
35 Shah, C., Oh, S., & Oh, J. S. (2009). Research agenda for social Q&A, Library and Information Science Research, 31, 205-209.   DOI   ScienceOn
36 Shatford, S. (1986). Analyzing the subject of a picture: A theoretical approach. Cataloging and Classification Quarterly, 6(3), 39-62. http://dx.doi.org/10.1300/J104v06n03_04   DOI   ScienceOn
37 Shatford-Layne, S. (1994). Some issues in the indexing of images. Journal of the American Society for Information Science, 45(8), 583-588.   DOI
38 Svenonius, E. (1994). Access to nonbook materials: The limits of subject indexing for visual and aural languages. Journal of the American Society for Information Science, 45(8), 600-606.   DOI
39 Savolainen, R. (1995). Everyday life information seeking: Approaching information seeking in the context of "way of life". Library and Information Science Research, 17, 259-294.   DOI   ScienceOn
40 Westman, S. (2009). Image users' needs and searching behavior. In A. Goker and J. Davies (eds), Information retrieval: Searching in the 21st century. John Wiley & Sons, Chichester.
41 Westman, S., Laine-Hernandez, M., & Oittinen, P. (2011). Development and evaluation of a multifaceted magazine image categorization model. Journal of the American Society for Information Science and Technology, 62(2), 295-313. http://dx.doi.org/10.1002/asi.21463   DOI   ScienceOn
42 Westman, S., & Oittinen, P. (2006). Image retrieval by end-users and intermediaries in a journalistic work context. Proceedings of the 1st International Conference on Information Interaction in Context, 102-110. http://dx.doi.org/10.1145/1164820.1164843   DOI
43 Yoon, J. (2011). Searching images in daily life. Library & Information Science Research, 33, 269-275. http://dx.doi.org/10.1016/j.lisr.2011.02.003   DOI   ScienceOn