TY - GEN
T1 - Using implicit relevane feedback to advance web image search
AU - En, Cheng
AU - Feng, Jing
AU - Mingjing, Li
AU - Weiying, Ma
AU - Hai, Jin
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2006
Y1 - 2006
N2 - Although relevance feedback has been extensively studied in content-based image retrieval in the academic area, no commercial web image search engine has employed the idea. There are several obstacles for Web image search engines in applying relevance feedback. To overcome these obstacles, we proposed an efficient implicit relevance feedback mechanism. The proposed mechanism shows advantage over traditional relevance feedback methods in the following three aspects. Firstly, instead of enforcing the users to make explicit judgment on the results, our method regards user's click-through data as implicit relevance feedback which release burden from users. Secondly, a hierarchical image search results clustering algorithm is proposed to semantically organize the search results. Using the clustering results as features, our relevance feedback scheme could catch and reflect users' search intention precisely. Lastly, unlike traditional relevance feedback user interface which hardily substitutes subsequent results for previous ones, our method employed friendly recommendation rather than substitution to let the user narrow down on the refined images. To evaluate the implicit relevance feedback mechanism, comprehensive user studies were performed. © 2006 IEEE.
AB - Although relevance feedback has been extensively studied in content-based image retrieval in the academic area, no commercial web image search engine has employed the idea. There are several obstacles for Web image search engines in applying relevance feedback. To overcome these obstacles, we proposed an efficient implicit relevance feedback mechanism. The proposed mechanism shows advantage over traditional relevance feedback methods in the following three aspects. Firstly, instead of enforcing the users to make explicit judgment on the results, our method regards user's click-through data as implicit relevance feedback which release burden from users. Secondly, a hierarchical image search results clustering algorithm is proposed to semantically organize the search results. Using the clustering results as features, our relevance feedback scheme could catch and reflect users' search intention precisely. Lastly, unlike traditional relevance feedback user interface which hardily substitutes subsequent results for previous ones, our method employed friendly recommendation rather than substitution to let the user narrow down on the refined images. To evaluate the implicit relevance feedback mechanism, comprehensive user studies were performed. © 2006 IEEE.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-34247570489&origin=recordpage
U2 - 10.1109/ICME.2006.262895
DO - 10.1109/ICME.2006.262895
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 1424403677
SN - 9781424403677
VL - 2006
T3 - 2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings
SP - 1773
EP - 1776
BT - 2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings
T2 - 2006 IEEE International Conference on Multimedia and Expo, ICME 2006
Y2 - 9 July 2006 through 12 July 2006
ER -