TY - GEN
T1 - A query analytic model for image retrieval
AU - Pu, Hsiao Tieh
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2004.
PY - 2005
Y1 - 2005
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=35048832434&partnerID=8YFLogxK
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U2 - 10.1007/978-3-540-30544-6_140
DO - 10.1007/978-3-540-30544-6_140
M3 - Conference contribution
AN - SCOPUS:35048832434
SN - 9783540240303
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 378
EP - 387
BT - Digital Libraries
A2 - Miao, Qihao
A2 - Lim, Ee-peng
A2 - Chen, Zhaoneng
A2 - Fu, Yuxi
A2 - Chen, Hsinchun
A2 - Fox, Edward
PB - Springer Verlag
T2 - 7th International Conference on Asian Digital Libraries, ICADL 2004
Y2 - 13 December 2004 through 17 December 2004
ER -