DOI 10.1007/s10994-009-5166-y A process for predicting manhole events in Manhattan

DOI 10.1007/s10994-009-5166-y A process for predicting manhole events in Manhattan (2010)

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by Cynthia Rudin , Rebecca J. Passonneau , Axinia Radeva , Haimonti Dutta , Steve Ierome , Delfina Isaac , C. Rudin , R. J. Passonneau , A. Radeva , H. Dutta , R. J. Passonneau , A. Radeva , H. Dutta , S. Ierome , D. Isaac , S. Ierome , D. Isaac

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Datum	Value	Source
TITLE	DOI 10.1007/s10994-009-5166-y A process for predicting manhole events in Manhattan	SVM HeaderParse 0.2
AUTHOR NAME	Cynthia Rudin	SVM HeaderParse 0.2
AUTHOR NAME	Rebecca J. Passonneau	SVM HeaderParse 0.2
AUTHOR NAME	Axinia Radeva	SVM HeaderParse 0.2
AUTHOR NAME	Haimonti Dutta	SVM HeaderParse 0.2
AUTHOR NAME	Steve Ierome	SVM HeaderParse 0.2
AUTHOR NAME	Delfina Isaac	SVM HeaderParse 0.2
AUTHOR NAME	C. Rudin	SVM HeaderParse 0.2
AUTHOR AFFIL	MIT Sloan School of Management, E53-323, Massachusetts Institute of Technology, Cambridge,	SVM HeaderParse 0.2
AUTHOR ADDR	MA 02139, USA	SVM HeaderParse 0.2
AUTHOR NAME	R. J. Passonneau	SVM HeaderParse 0.2
AUTHOR AFFIL	Center for Computational Learning Systems, Columbia University, 475 Riverside Dr., New York,	SVM HeaderParse 0.2
AUTHOR ADDR	NY 10115, USA	SVM HeaderParse 0.2
AUTHOR NAME	A. Radeva	SVM HeaderParse 0.2
AUTHOR AFFIL	Center for Computational Learning Systems, Columbia University, 475 Riverside Dr., New York,	SVM HeaderParse 0.2
AUTHOR ADDR	NY 10115, USA	SVM HeaderParse 0.2
AUTHOR NAME	H. Dutta	SVM HeaderParse 0.2
AUTHOR AFFIL	Center for Computational Learning Systems, Columbia University, 475 Riverside Dr., New York,	SVM HeaderParse 0.2
AUTHOR ADDR	NY 10115, USA	SVM HeaderParse 0.2
AUTHOR NAME	R. J. Passonneau	SVM HeaderParse 0.2
AUTHOR NAME	A. Radeva	SVM HeaderParse 0.2
AUTHOR NAME	H. Dutta	SVM HeaderParse 0.2
AUTHOR NAME	S. Ierome	SVM HeaderParse 0.2
AUTHOR ADDR	Consolidated Edison Company of New York, 4 Irving Place, New York, NY 10003, USA	SVM HeaderParse 0.2
AUTHOR NAME	D. Isaac	SVM HeaderParse 0.2
AUTHOR ADDR	Consolidated Edison Company of New York, 4 Irving Place, New York, NY 10003, USA	SVM HeaderParse 0.2
AUTHOR NAME	S. Ierome	SVM HeaderParse 0.2
AUTHOR NAME	D. Isaac	SVM HeaderParse 0.2
ABSTRACT	Abstract We present a knowledge discovery and data mining process developed as part of the Columbia/Con Edison project on manhole event prediction. This process can assist with real-world prioritization problems that involve raw data in the form of noisy documents requiring significant amounts of pre-processing. The documents are linked to a set of instances to be ranked according to prediction criteria. In the case of manhole event prediction, which is a new application for machine learning, the goal is to rank the electrical grid structures in Manhattan (manholes and service boxes) according to their vulnerability to serious manhole	SVM HeaderParse 0.2
YEAR	2010	SVM HeaderParse 0.2
CITATIONS	43 found	ParsCit 1.0