On Approximately Searching for Similar Word Embeddings

被引：0

作者：

Sugawara, Kohei ^{[1
]}

Kobayashi, Hayato ^{[1
]}

Iwasaki, Masajiro ^{[1
]}

机构：

[1] Yahoo Japan Corp, Chiyoda Ku, 1-3 Kioicho, Tokyo 1028282, Japan

来源：

PROCEEDINGS OF THE 54TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 1 | 2016年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We discuss an approximate similarity search for word embeddings, which is an operation to approximately find embeddings close to a given vector. We compared several metric-based search algorithms with hash-, tree-, and graph-based indexing from different aspects. Our experimental results showed that a graph-based indexing exhibits robust performance and additionally provided useful information, e.g., vector normalization achieves an efficient search with cosine similarity.

引用

页码：2265 / 2275

页数：11

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