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English(EN) SOLO: Certified-Recall Metric Similarity Search with Scan-Only Sampled Inverted Lists

SOLO索引通过扫描式采样倒排列表提供认证召回率，并减少内存占用

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员推出了一种新颖的度量空间近似最近邻搜索索引SOLO，它无需启发式排序即可提供认证召回率。该方法直接从索引本身计算召回率，能够通过对查询样本进行真实值传递来认证所有操作点的性能。与HNSW、DiskANN和SPANN等现有方法相比，SOLO在吞吐量方面具有竞争力，并且内存使用量显著减少，在大型数据集上以最小的内存占用实现了高召回率。 AI

影响 这种新的索引方法可以显著提高大规模相似性搜索系统的效率并减少其内存占用，从而影响推荐引擎和语义搜索等领域。

排序理由 该集群包含一个学术论文的两个版本，详细介绍了一种新的相似性搜索方法。

在 arXiv cs.IR (Information Retrieval) 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

SOLO索引通过扫描式采样倒排列表提供认证召回率，并减少内存占用

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该集群包含一个学术论文的两个版本，详细介绍了一种新的相似性搜索方法。
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报道来源 [2]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Édgar Chávez ·

    SOLO: 具有仅扫描采样倒排列表的认证召回度量相似性搜索

    We present SOLO, an index for approximate nearest-neighbor search in general metric spaces whose serving path contains no ranking heuristic of any kind: a query is routed to the $k_s$ nearest points of a random sample of the database, and every object in the touched posting lists…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Édgar Chávez ·

    SOLO：具有仅扫描采样倒排列表的认证召回度量相似性搜索

    In every fast nearest-neighbor index, recall is measured, never predicted: each operating point is tuned by serving it against ground truth. SOLO is an index whose recall is computed from the index itself, before any query is served. SOLO is an inverted file whose vocabulary is a…

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