On Approximately Searching for Similar Word Embeddings
Kohei Sugawara, Hayato Kobayashi, Masajiro Iwasaki · 2016
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 graphbased 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.