TY - JOUR
T1 - (Artificial) Mind over matter
T2 - 2020 International Conference on Very Large Databases PhD Workshop, VLDB-PhD 2020
AU - Shraga, Roee
AU - Gal, Avigdor
AU - Ackerman, Rakefet
N1 - Publisher Copyright:
Copyright © 2020 for this paper by its authors. Copying permitted for private and academic purposes.
PY - 2020
Y1 - 2020
N2 - The matching task is at the heart of data integration, in charge of aligning elements of data sources. Historically, matching problems were considered semi automated tasks in which correspondences are generated by matching algorithms and subsequently validated by human expert(s). This research is devoted to the changing role of humans in matching, which is divided into two main approaches, namely Humans Out and Humans In. With the increase in amount and size of matching tasks, the role of humans as validators seems to diminish; thus Humans In questions the inherent need for humans in the matching loop. On the other hand, Humans Out focuses on overcoming human cognitive biases via algorithmic assistance. Above all, we observe that matching requires unconventional thinking demonstrated by advance machine learning methods to complement (and possibly take over) the role of humans in matching.
AB - The matching task is at the heart of data integration, in charge of aligning elements of data sources. Historically, matching problems were considered semi automated tasks in which correspondences are generated by matching algorithms and subsequently validated by human expert(s). This research is devoted to the changing role of humans in matching, which is divided into two main approaches, namely Humans Out and Humans In. With the increase in amount and size of matching tasks, the role of humans as validators seems to diminish; thus Humans In questions the inherent need for humans in the matching loop. On the other hand, Humans Out focuses on overcoming human cognitive biases via algorithmic assistance. Above all, we observe that matching requires unconventional thinking demonstrated by advance machine learning methods to complement (and possibly take over) the role of humans in matching.
UR - http://www.scopus.com/inward/record.url?scp=85090505575&partnerID=8YFLogxK
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AN - SCOPUS:85090505575
SN - 1613-0073
VL - 2652
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
Y2 - 31 August 2020 through 4 September 2020
ER -