- P-ISSN1013-0799
- E-ISSN2586-2073
- KCI
An Approach Toward Image Access Points based on Image Needs in Context of Everyday Life
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, image, information needs, everyday life, information behavior, searching model, indexing, access point, social Q&A, 이미지, 정보요구, 일상생활, 정보행동, 탐색모델, 색인, 접근점, 소셜 Q&A
Reference
이지연. (2002). 이용자 관점에서 본 이미지 색인의 객관성에 대한 연구. 정보관리학회지, 19(3), 123-143.
Beaudoin, 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.
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.
Chen, H.. (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.
Choi, Y.. (2010). Effects of contextual factors on image searching. Journal of the American Society for Information Science and Technology, 61(10), 2011-2028.
Choi, Y.. (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.
정은경. (2010). A Preliminary Examination on the Multimedia Information Needs and Web Searches of College Students in Korea. 한국문헌정보학회지, 44(4), 95-114.
정은경. (201104). Image needs in the context of image use: An exploratory study. JOURNAL OF INFORMATION SCIENCE, 37(2), 163-177.
Conniss, L. R.. (2000). Information seeking behavior : Visor I final report. Newcastle upon Tyne.
Cunningham, S. J.. (2004). How people describe their image information needs : A grounded theory analysis of visual arts queries (47-48). Proceedings of the Joint Conference on Digital Libraries.
Cunningham, S. J.. (2006). Looking for a picture: An analysis of everyday image information searching (198-199). Proceedings of the 6th ACM/IEEE-CS Joint Conference On Digital Libraries.
Eakins, J.. (2004). Image retrieval interfaces : A user perspective. Lecture Notes in Computer Science, 3115, 628-637.
Enser, P. G. B.. (1992). Analysis of visual information retrieval queries: British Library R&D Report No. 6104. .
Enser, P. G. B.. (1995). Pictorial information retrieval. Journal of Documentation, 51(2), 126-170.
Enser, P. G. B.. (2007). Facing the reality of semantic image retrieval. Journal of Documentation, 63(4), 465-481.
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.
Fukumoto, T.. (2006). An analysis of image retrieval behavior for metadata type image database. Information Processing and Management, 42, 723-728.
Goodrum, A.. (2001). Image searching on the Excite Web search engine. Information Processing and Management, 37, 295-311.
Hasting, S. K.. (1995). Query categories in a study of intellectual access to digitized art images (3-8). Proceedings of the 58th Annual Meeting of the American Society for Information Science.
Hollink, L.. (2004). Classification of user image descriptions. International Journal of Human-Computer Studies, 61, 601-626.
Jamies, A.. (2006). Human factors in automatic image retrieval system design and evaluation (101-109). Proceedings of IS&T/SPIE Internet Imaging Ⅶ.
Jamies, A.. (2000). A conceptual framework for indexing visual information at multiple levels (2-15). IS&T/SPIE Internet Imaging.
Jensen, B. J.. (2008). Searching for digital images on the web. Journal of Documentation, 64(1), 81-101.
Jean, B. St.. (2012). An analysis of the information behaviors, goals, and intentions of frequent Internet users: Findings from online activity diaries. First Monday, 17(2), -.
Jörgensen, C.. (1998). Attributes of images in describing tasks. Information Processing & Management, 34(2), 161-174.
Jörgensen, 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.
Krause, M. C.. (1998). Intellectual problems of indexing picture collections. Audiovisual Librarian, 14(2), 73-81.
Markkula, M.. (2000). End-user searching challenges indexing practices in the digital newspaper photo archive. Information Retrieval, 1(4), 250-285.
McCay-Peet, L.. (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.
Oranger, S.. (1995). The newspaper image database: Empirical supported analysis of users' typology and word association clusters (212-218). Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’95).
Panofsky, E.. (1962). Studies in iconology : Humanistic themes in the art of renaissance:Harper & Rowe.
Pu, H.. (2005). A comparative analysis of web image and textual queries. Online Information Review, 29(5), 457-467.
Schlak, T.. (2010). Image retrieval as information seeking behavior? Self-categorizations of user motivations to retrieve images.
서은경. (2008). The Access-Enhanced Search Interface Design for Korean Paintings. 정보관리학회지, 25(2), 25-48.
Shah, C.. (2009). Research agenda for social Q&A. Library and Information Science Research, 31, 205-209.
Shatford, S.. (1986). Analyzing the subject of a picture: A theoretical approach. Cataloging and Classification Quarterly, 6(3), 39-62.
Shatford-Layne, S.. (1994). Some issues in the indexing of images. Journal of the American Society for Information Science, 45(8), 583-588.
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.
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.
Westman, S.. (2009). Image users' needs and searching behavior, In Information retrieval: Searching in the 21st century:John Wiley & Sons.
Westman, S.. (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.
Westman, S.. (2006). Image retrieval by end-users and intermediaries in a journalistic work context (102-110). Proceedings of the 1st International Conference on Information Interaction in Context.
Yoon, J.. (2011). Searching images in daily life. Library & Information Science Research, 33, 269-275.
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