NDLI: Study on Feature Extraction in China Railway Ticketing and Reservation System

Content Provider	IEEE Xplore Digital Library
Author	Xiaoyan Lui Chunhuang Liu Weiwei Wang
Copyright Year	2007
Description	Author affiliation: China Acad. of Railway Sci., Beijing (Xiaoyan Lui; Chunhuang Liu; Weiwei Wang)
Abstract	Because that data analysis methods for train ticket data are mostly designed for building predictive analysis models, which are always good at describing the characteristics of major classes but are lack of reflecting the minorities, this paper presents a new method FEBIR that is based on the set-partition for data feature extraction. The presented method can distill the pointed favorite class features without the limitations of current analysis methods in characterizing the minors. The characteristic rules which are extracted by this method include quantitative information, and the order of attributes in the rules reflects how importantly they contribute to sculpture the class, so it provides enough information for decision-makers to analyze the special class and will be an effective tool for railway managers to get useful information about their focuses.
Starting Page	689
Ending Page	693
File Size	293404
Page Count	5
File Format	PDF
ISBN	9780769528748
DOI	10.1109/FSKD.2007.540
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computers Data analysis Voting Buildings Predictive models Feature extraction Rail transportation Data mining Decision trees Information analysis
Content Type	Text
Resource Type	Article

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