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    • 2. 发明授权
    • Content search with category-aware visual similarity
    • 内容搜索与类别感知视觉相似性
    • US08990199B1
    • 2015-03-24
    • US12895601
    • 2010-09-30
    • Sunil RameshArnab S. DhuaSupratik BhattacharyyaGurumurthy D. RamkumarGautam Bhargava
    • Sunil RameshArnab S. DhuaSupratik BhattacharyyaGurumurthy D. RamkumarGautam Bhargava
    • G06F7/00G06F17/30
    • G06F17/30259G06F17/30256G06F17/30864
    • Visual incongruity in search result sets may be reduced at least in part by searching an optimized visually significant subset of a category tree that categorizes a collection of content. The category tree may be optimized at build time at least in part by pruning with respect to visual coherence and by the size of the content collection subset referenced by particular categories. Content collection subset sizes both too large and too small can detract from the visual significance of a particular category. The visually significant subset of the category tree may be further optimized at query time by intersecting the visually significant subset with the query-associated sub-tree(s) and further pruning categories in the visually significant subset that have child categories in the visually significant subset. Searching with respect to the optimized visually significant subset can also improve search efficiency.
    • 搜索结果集中的视觉不协调可以至少部分地通过搜索对内容集合进行分类的类别树的优化的视觉上重要的子集来减少。 类别树可以在构建时间至少部分地通过针对视觉一致性的修剪以及由特定类别引用的内容收集子集的大小进行优化。 内容收集子集大小太大和太小可能会降低特定类别的视觉含义。 可以在查询时间通过将视觉上有意义的子集与查询关联的子树相交并在视觉上有意义的子集中进一步修剪在视觉上有意义的子集中具有子类别的视觉上重要子集中的类别,来进一步优化类别树的视觉上重要的子集 。 关于优化的视觉显着子集的搜索也可以提高搜索效率。