A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2006; you can also visit the original URL.
The file type is
It has been established that active learning is effective for learning complex, subjective query concepts for image retrieval. However, active learning has been applied in a concept independent way, (i.e., the kernel-parameters and the sampling strategy are identically chosen) for learning query concepts of differing complexity. In this work, we first characterize a concept's complexity using three measures: hitrate, isolation and diversity. We then propose a multimodal learning approach thatdoi:10.1145/1027527.1027664 dblp:conf/mm/GohCL04 fatcat:yq5qccle7vf7dnkiz65j2ttx7a