Learning query-space document representations for high-recall retrieval

Sara Salamat, Negar Arabzadeh, Fattane Zarrinkalam, Morteza Zihayat, Ebrahim Bagheri
January 2023

Abstract

This paper presents methods for learning query-space document representations for high-recall retrieval, improving search completeness and coverage.

Type
Conference paper
Publication
European Conference on Information Retrieval

This work introduces query-space representation learning for high-recall retrieval.

Query-Space Representations Document Representations High-Recall Retrieval Learning Methods Information Retrieval
Morteza Zihayat
Morteza Zihayat
Principal Investigator

Dr. Morteza Zihayat is a Canada Research Chair (CRC) in Human-Centered AI and Associate Professor at Toronto Metropolitan University, Faculty of Engineering and Architectural Science. He also holds appointments as Adjunct Associate Professor at the University of Waterloo (Management Sciences) and IBM Faculty Fellow at IBM Centre for Advanced Studies. He is the Director of the Human-Centered Machine Intelligence Lab.