Optimizing video search reranking via minimum incremental information loss

@inproceedings{Liu2008OptimizingVS,
  title={Optimizing video search reranking via minimum incremental information loss},
  author={Yuan Liu and Tao Mei and Xiuqing Wu and Xian-Sheng Hua},
  booktitle={Multimedia Information Retrieval},
  year={2008}
}
This paper is concerned with video search reranking - the task of reordering the initial ranked documents (video shots) to improve the search performance - in an optimization framework. Conventional supervised reranking approaches empirically convert the reranking as a classification problem in which each document is determined relevant or not, followed by reordering the documents according to the confidence scores of classification. We argue that reranking is essentially an optimization… CONTINUE READING
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