176 citations · 914 across the 61 of their papers we have counts for
3 papers · 2 filters
Learning to Match Using Local and Distributed Representations of Text for Web Search
Bhaskar Mitra, Fernando Diaz, Nick Craswell
Models such as latent semantic analysis and those based on neural embeddings learn distributed representations of text, and match the query against the document in the latent seman…
Query Expansion with Locally-Trained Word Embeddings
Fernando Diaz, Bhaskar Mitra, Nick Craswell
Continuous space word embeddings have received a great deal of attention in the natural language processing and machine learning communities for their ability to model term similar…
A Dual Embedding Space Model for Document Ranking
Bhaskar Mitra, Eric Nalisnick, Nick Craswell +1
A fundamental goal of search engines is to identify, given a query, documents that have relevant text. This is intrinsically difficult because the query and the document may use di…