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Towards Next Generation Multimedia Information Retrieval by Analyzing User-centered Image Access and Use

Journal of the Korean Society for Library and Information Science / Journal of the Korean Society for Library and Information Science, (P)1225-598X; (E)2982-6292
2017, v.51 no.4, pp.121-138
https://doi.org/10.4275/KSLIS.2017.51.4.121

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Abstract

As information users seek multimedia with a wide variety of information needs, information environments for multimedia have been developed drastically. More specifically, as seeking multimedia with emotional access points has been popular, the needs for indexing in terms of abstract concepts including emotions have grown. This study aims to analyze the index terms extracted from Getty Image Bank. Five basic emotion terms, which are sadness, love, horror, happiness, anger, were used when collected the indexing terms. A total 22,675 index terms were used for this study. The data are three sets; entire emotion, positive emotion, and negative emotion. For these three data sets, co-word occurrence matrices were created and visualized in weighted network with PNNC clusters. The entire emotion network demonstrates three clusters and 20 sub-clusters. On the other hand, positive emotion network and negative emotion network show 10 clusters, respectively. The results point out three elements for next generation of multimedia retrieval: (1) the analysis on index terms for emotions shown in people on image, (2) the relationship between connotative term and denotative term and possibility for inferring connotative terms from denotative terms using the relationship, and (3) the significance of thesaurus on connotative term in order to expand related terms or synonyms for better access points.

keywords
이미지 검색, 감정 색인, 멀티미디어, 이미지, 네트워크분석, 동시출현단어분석, Image Retrieval, Emotion Indexing, Multimedia, Image, Network Analysis, Co-word Occurrence Analysis

Reference

1.

이재윤. 2006. 지적 구조 분석을 위한 새로운 클러스터링 기법에 관한 연구. 정보관리학회지, 23(4), 215-231.

2.

이재윤. COOC ver 0.4 프로그램 [cited 2017. 10. 7.]

3.

이재윤. WNET ver 0.4.1 프로그램 [cited 2017. 10. 7.]

4.

정선영, 정은경. 2014. 이미지 감정색인을 위한 시각적 요인 분석에 관한 탐색적 연구. 한국문헌정보학회지, 48(1), 53-73.

5.

정은경. 2014. 이용자 반응 기반 이미지 감정 접근점 확장에 관한 연구. 한국비블리아학회지, 25(3), 101-118.

6.

Chang, S. L., and Lee, Y. 2001. Conceptualizing Context and Its Relationship to the Information Behaviour in Dissertation Research Process. The New Review of Information Behavior Research, 2(November), 29-46.

7.

Choi, Y. 2010. Effects of Contextual Factors on Image Searching on the Web. Journal of the American Society for Information Science and Technology, 61(10), 2011-2028.

8.

Chung, E., and Yoon, J. 2009. Categorical and Specificity Differences between User-supplied Tags and Search Query Terms for Images. An Analysis of Flickr Tags and Web Image Search Queries. Information Research: An International Electronic Journal, 14(3), 403-430.

9.

Chung, E., and Yoon, J. 2011. Image Needs in the Context of Image Use: An Exploratory Study. Journal of Information Science, 37(2), 163-177.

10.

Chung, E., and Yoon, J. 2013. An Analysis of Image Use in Twitter Message. Journal of the Korean Biblia Society for Library and Information Science, 24(4), 75-90.

11.

Connis, L. R., Ashford, A. J., and Graham, M. E. 2002. Information Seeking Behavior in Image Retrieval: VISOR I Final Report. Art Libraries Journal, 27(2), 46-47.

12.

Coutright, C. 2007. Context in Information Behavior Research. The Annual Review of Information Science and Technology, 41(1), 273-306.

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.

14.

Johnson, J. D. 2003. On Contexts of Information Seeking. Information Processing and Management, 39, 735-760.

15.

Knautz, K., and Stock, W. G. 2011. Collective Indexing of Emotions in Videos. Journal of Documentation, 67(6), 975-994.

16.

Matusiak, K. K. 2006. Towards User-centered Indexing in Digital Image Collections. OCLC Systems & Services: International Digital Library Perspectives, 22(4), 283-298.

17.

McCay-Peet, L., and 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.

18.

Ménard, E., and Smithglass, M. 2012. Digital Image Description: a Review of Best Practices in Cultural Institutions. Library Hi Tech, 30(2), 291-309.

19.

Rho, S., and Yeo, S. S. 2013. Bridging the Semantic Gap in Multimedia Emotion/Mood Recognition for Ubiquitous Computing Environment. The Journal of Supercomputing, 65(1), 274-286.

20.

Rorissa, A. 2008. User-generated Descriptions of Individual Images versus Labels of Groups of Images: A Comparison using Basic Level Theory. Information Processing & Management, 44(5), 1741-1753.

21.

Rorissa, A. 2010. A Comparative Study of Flickr Tags and Index Terms in a General Image Collection. Journal of the American Society for Information Science and Technology, 61(11), 2230-2242.

22.

St. Jean, B. et al. 2012. An Analysis of the Information Behavior, Goals, and Intentions of Frequent Internet Users: Findings from Online Activity Diaries. First Monday, 17(2). [online] [cited 2017. 10. 5.]<http://firstmonday.org/ojs/index.php/fm/article/view/3870/3143>

23.

Stvilia, B., Jörgensen, C., and Wu, S. 2012. Establishing the Value of Socially-created Metadata to Image Indexing. Library and Information Science Research, 34(2), 99-109.

24.

Tao, J., and Tan, T. 2005. Affective Computing: A Review. Quoted in Tao, J., Tan, T., and Picard R.W. eds. 2005. Affective Computing and Intelligent Interaction." In Proceedings of the 1st International Conference, ACII 2005, Beijing, October 22-24, 2005, Beijing. Heidelberg:Springer-Verlag.

25.

Westman, S., and Oittinen, P. 2006. Image Retrieval by End-users and Intermediaries in a Journalistic Work Context. In Proceedings of the 1st International Conference on Information Interaction in Context, October 18-20, 2006, Copenhagen: 102-110.

26.

Yoon, J. 2006. An Exploration of Needs for Connotative Messages during Image Search Process. Proceedings of the Association for Information Science and Technology, 43(1), 1-19.

27.

Yoon, J., and O'Connor, B. 2010. Engineering an Image-browsing Environment: Re-purposing Existing Denotative Descriptors. Journal of Documentation, 66(5), 750-774.

Journal of the Korean Society for Library and Information Science