Sept. 19, 2022, 1:15 a.m. | David Wadden, Nikita Gupta, Kenton Lee, Kristina Toutanova

cs.CL updates on arXiv.org arxiv.org

We introduce the task of entity-centric query refinement. Given an input
query whose answer is a (potentially large) collection of entities, the task
output is a small set of query refinements meant to assist the user in
efficient domain exploration and entity discovery. We propose a method to
create a training dataset for this task. For a given input query, we use an
existing knowledge base taxonomy as a source of candidate query refinements,
and choose a final set of …

arxiv query

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Social Insights & Data Analyst (Freelance)

@ Media.Monks | Jakarta

Cloud Data Engineer

@ Arkatechture | Portland, ME, USA