Compared to the traditional functional dependency (FD), the extended conditional functional dependency (CFD) has shown greater potential for detecting and repairing inconsistent data. CFDMiner is a widely used algorithm for mining constant-CFDs. But the search space of CFDMiner is too large, and there is still room for efficiency improvement. In this paper, an efficient pruning strategy is proposed to optimize the algorithm by reducing the search space. Both theoretical analysis and experiments have proved the optimized algorithm can produce the consistent results as the original CFDMiner.
Jinling ZHOU
PLA University of Science and Technology
Xingchun DIAO
PLA University of Science and Technology
Jianjun CAO
PLA University of Science and Technology
Zhisong PAN
PLA University of Science and Technology
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Jinling ZHOU, Xingchun DIAO, Jianjun CAO, Zhisong PAN, "An Optimization Strategy for CFDMiner: An Algorithm of Discovering Constant Conditional Functional Dependencies" in IEICE TRANSACTIONS on Information,
vol. E99-D, no. 2, pp. 537-540, February 2016, doi: 10.1587/transinf.2015EDL8170.
Abstract: Compared to the traditional functional dependency (FD), the extended conditional functional dependency (CFD) has shown greater potential for detecting and repairing inconsistent data. CFDMiner is a widely used algorithm for mining constant-CFDs. But the search space of CFDMiner is too large, and there is still room for efficiency improvement. In this paper, an efficient pruning strategy is proposed to optimize the algorithm by reducing the search space. Both theoretical analysis and experiments have proved the optimized algorithm can produce the consistent results as the original CFDMiner.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2015EDL8170/_p
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@ARTICLE{e99-d_2_537,
author={Jinling ZHOU, Xingchun DIAO, Jianjun CAO, Zhisong PAN, },
journal={IEICE TRANSACTIONS on Information},
title={An Optimization Strategy for CFDMiner: An Algorithm of Discovering Constant Conditional Functional Dependencies},
year={2016},
volume={E99-D},
number={2},
pages={537-540},
abstract={Compared to the traditional functional dependency (FD), the extended conditional functional dependency (CFD) has shown greater potential for detecting and repairing inconsistent data. CFDMiner is a widely used algorithm for mining constant-CFDs. But the search space of CFDMiner is too large, and there is still room for efficiency improvement. In this paper, an efficient pruning strategy is proposed to optimize the algorithm by reducing the search space. Both theoretical analysis and experiments have proved the optimized algorithm can produce the consistent results as the original CFDMiner.},
keywords={},
doi={10.1587/transinf.2015EDL8170},
ISSN={1745-1361},
month={February},}
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TY - JOUR
TI - An Optimization Strategy for CFDMiner: An Algorithm of Discovering Constant Conditional Functional Dependencies
T2 - IEICE TRANSACTIONS on Information
SP - 537
EP - 540
AU - Jinling ZHOU
AU - Xingchun DIAO
AU - Jianjun CAO
AU - Zhisong PAN
PY - 2016
DO - 10.1587/transinf.2015EDL8170
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2016
AB - Compared to the traditional functional dependency (FD), the extended conditional functional dependency (CFD) has shown greater potential for detecting and repairing inconsistent data. CFDMiner is a widely used algorithm for mining constant-CFDs. But the search space of CFDMiner is too large, and there is still room for efficiency improvement. In this paper, an efficient pruning strategy is proposed to optimize the algorithm by reducing the search space. Both theoretical analysis and experiments have proved the optimized algorithm can produce the consistent results as the original CFDMiner.
ER -