TY - GEN
T1 - In schema matching, even experts are human
T2 - 2014 IEEE 30th International Conference on Data Engineering Workshops, ICDEW 2014
AU - Sagi, Tomer
AU - Gal, Avigdor
PY - 2014
Y1 - 2014
N2 - Schema matching problems have been historically defined as a semi-automated task in which correspondences are generated by matching algorithms and subsequently validated by a single human expert. Emerging alternative models are based upon piecemeal human validation of algorithmic results and the usage of crowd based validation. We propose an alternative model in which human and algorithmic matchers are given more symmetric roles. Under this model, better insight into the respective strengths and weaknesses of human and algorithmic matchers is required. We present initial insights from a pilot study conducted and outline future work in this area.
AB - Schema matching problems have been historically defined as a semi-automated task in which correspondences are generated by matching algorithms and subsequently validated by a single human expert. Emerging alternative models are based upon piecemeal human validation of algorithmic results and the usage of crowd based validation. We propose an alternative model in which human and algorithmic matchers are given more symmetric roles. Under this model, better insight into the respective strengths and weaknesses of human and algorithmic matchers is required. We present initial insights from a pilot study conducted and outline future work in this area.
UR - http://www.scopus.com/inward/record.url?scp=84901762360&partnerID=8YFLogxK
U2 - 10.1109/ICDEW.2014.6818301
DO - 10.1109/ICDEW.2014.6818301
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AN - SCOPUS:84901762360
SN - 9781479934805
T3 - Proceedings - International Conference on Data Engineering
SP - 45
EP - 49
BT - 2014 IEEE 30th International Conference on Data Engineering Workshops, ICDEW 2014
Y2 - 31 March 2014 through 4 April 2014
ER -