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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hoon Yul Bang Cha Zhang Tsuhan Chen |
| Copyright Year | 2004 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA (Hoon Yul Bang; Cha Zhang; Tsuhan Chen) |
| Abstract | Relevance feedback has been a very useful tool to enhance the performance of content-based information retrieval (CBIR) systems. To fully make use of the precious user feedback provided to a system, we propose an approach named semantic propagation, which reveals the deep semantic relationships among objects in the database, given a set of relevance feedbacks between object pairs. In particular, we present two semantic propagation algorithms that are applicable to CIBR systems with a feature vector space model and a general metric space model, respectively. Experiments on a 3D model retrieval system and a logo image retrieval system are performed to show the effectiveness of the proposed methods. |
| Starting Page | 81 |
| Ending Page | 84 |
| File Size | 295874 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780386035 |
| DOI | 10.1109/ICME.2004.1394130 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-06-27 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Information retrieval Spatial databases Extraterrestrial measurements Content based retrieval Image retrieval Negative feedback Image databases Feature extraction Data mining Indexing |
| Content Type | Text |
| Resource Type | Article |
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