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Using High Dimensional Indexes to Support Relevance Feedback Based Interactive Images Retrieval

Summary: Tackles semantic gap in image retrieval via relevance feedback, using high-dimensional indexes to boost precision and recall. Proposes a B+-tree-like index with cluster splitting and iDistance; demo analyzes adaptive distance updates and index efficiency. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9602
Venue
VLDB
Year
2006
Pagerank
5.093636e-05
Overall Rank
12,704 | 12.84%
DOI
-

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BibTeX Citation

@article{zhang_vldb06,
        title = {{Using High Dimensional Indexes to Support Relevance Feedback Based Interactive Images Retrieval}},
        author = {Zhang, Junqi and Zhou, Xiangdong and Wang, Wei and Shi, Baile and Pei, Jian},
        journal = {PVLDB},
        series = {{VLDB} '06},
        pages = {1211--1214},
        year = {2006}
}

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