Are Embeddings Enough? SIRIP Panel on the Future of Embeddings in Industry IR Systems

In this article we introduce the notion of nearest-neighbor-preserving embeddings. These are randomized embeddings between two metric spaces which preserve the (approximate) nearest-neighbors. We give two examples of such embeddings for Euclidean ...

Ranking has been one of the most important tasks in information retrieval. With the development of deep representation learning, many researchers propose to encode both the query and items into embedding vectors and rank the items according to the inner ...

We present hash embeddings, an efficient method for representing words in a continuous vector form. A hash embedding may be seen as an interpolation between a standard word embedding and a word embedding created using a random hash function (the hashing ...