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Title: Erica: Query Refinement for Diversity Constraint Satisfaction
Relational queries are commonly used to support decision making in critical domains like hiring and college admissions. For example, a college admissions officer may need to select a subset of the applicants for in-person interviews, who individually meet the qualification requirements (e.g., have a sufficiently high GPA) and are collectively demographically diverse (e.g., include a sufficient number of candidates of each gender and of each race). However, traditional relational queries only support selection conditions checked against each input tuple, and they do not support diversity conditions checked against multiple, possibly overlapping, groups of output tuples. To address this shortcoming, we present Erica, an interactive system that proposes minimal modifications for selection queries to have them satisfy constraints on the cardinalities of multiple groups in the result. We demonstrate the effectiveness of Erica using several real-life datasets and diversity requirements.  more » « less
Award ID(s):
2106176
PAR ID:
10482057
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
VLDB
Date Published:
Journal Name:
Proceedings of the VLDB Endowment
Volume:
16
Issue:
12
ISSN:
2150-8097
Page Range / eLocation ID:
4070 to 4073
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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