Abstract
Searching digital images on a networked environment is rapidly growing. Despite recent advances in image retrieval technologies, high-precision and robust solutions remain hampered by limits to knowledge about user issues associated with image retrieval. This paper examines a large number of queries from a Web image search engine, and attempts to develop an analytic model to investigate their implications for image retrieval technologies. The model employs the concepts of uniqueness and refinement to categorize successful and failed queries. The results show that image requests have a higher specificity and may often contain queries refined by interpretive, reactive, and perceptual attributes. Based on the proposed model, the study further investigates feasible technical solutions integrating both content-based and concept-based technologies to deal with real image query types. The initial study has provided useful results that enhance the understanding of digital image searching and suggests implications for the improvement of image retrieval systems.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Brown, P., Hidderley, R., Griffin, H., Rollason, S.: The democratic indexing of images. The New Review of Hypermedia and Multimedia 2, 107–121 (1996)
Chen, H.: An analysis of image queries in the field of art history. Journal of the American Society for Information Science & Technology 52(3), 260–273 (2001)
Chien, L.-F., Pu, H.-T.: Important issues on Chinese information retrieval. Computational Linguistics and Chinese Language Processing 1(1), 205–221 (1996)
Choi, Y., Rasmussen, E.M.: Searching for images: The analysis of users’ queries for image retrieval in American history. Journal of the American Society for Information Science & Technology 54(6), 498–511 (2003)
Enser, P.G.B.: Progress in documentation: Pictorial information retrieval. Journal of Documentation 51(2), 126–170 (1995)
Enser, P.G.B.: Visual image retrieval: Seeking the alliance of concept-based and content-based paradigms. Journal of Information Science 26(4), 199–210 (2000)
Enser, P.G.M., McGregor, C.: Analysis of visual information retrieval queries. British Library Research and Development Report 6104 (1993)
Fidel, R.: The image retrieval task: Implications for the design and evaluation of image databases. The New Review of Hypermedia and Multimedia 3, 181–199 (1997)
Jansen, B.J., Spink, A., Saracevic, T.: Real life, real users, and real needs: A study and analysis of user queries on the web. Information Processing & Management 36(2), 207–227 (2000)
Jorgensen, C.: Attributes of images in describing tasks. Information Processing & Management 34(2/3), 161–174 (1998)
Pu, H.-T., Chuang, S.-L., Yang, C.: Subject categorization of query terms for exploring Web users’ search interests. Journal of the American Society for Information Science & Technology 53(8), 617–630 (2002)
Pu, H.-T.: An analysis of Web image queries for search. In: ASIST 2003, pp. 340–348 (2003)
Rasmussen, E.: Indexing images. Annual Review of Information Science and Technology 32, 169–196 (1997)
Sebe, N., Lew, M.S., Zhou, X.S., Huang, T.S., Bakker, E.M.: The state of the art in image and video retrieval. In: CIVR 2003, pp. 1–8 (2003)
Silverstein, C., Henzinger, M., Marais, H.,, Moricz, M.: Analysis of a very large Web search engine query log. SIGIR Forum 33(1), 6–12 (1999)
Smith, J., Chang, S.: An image and video search engine for the world wide web. In: Sethi, I., Jain, R. (eds.) Proceedings of SPIE, vol. 3022, pp. 84–95 (1997)
Taylor, R.S.: Question-negotiation and information seeking in libraries: The process of asking questions. College and Research Libraries 29, 178–194 (1968)
Tomaiuolo, N.G.: When image is everything. Searcher, 10(1) (2002), http://www.infotoday.com/searcher/jan02/tomaiuolo.htm
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pu, HT. (2004). A Query Analytic Model for Image Retrieval. In: Chen, Z., Chen, H., Miao, Q., Fu, Y., Fox, E., Lim, Ep. (eds) Digital Libraries: International Collaboration and Cross-Fertilization. ICADL 2004. Lecture Notes in Computer Science, vol 3334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30544-6_41
Download citation
DOI: https://doi.org/10.1007/978-3-540-30544-6_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24030-3
Online ISBN: 978-3-540-30544-6
eBook Packages: Computer ScienceComputer Science (R0)