NDLI: Study of text classification methods for data sets with huge features

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2010 2nd International Conference on Industrial and Information Systems

Volume 2 - 2010

Volume 1 - 2010

Support vector machine fuzzy self-learning control with self-adaptive chaotic optimal learning algorithm for induction machines

Notice of RetractionA study on Consensus algorithm of interdepartmental Consensus Formation

Online insurance's business process and marketing decision

Construction of industrial control network laboratory

The construction of integrated financial system in supply chain

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Study on the forecasting method of traffic violation black spot

A novel method for solving knapsack problem base on Hybrid Genetic Algorithm

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Analysis and structure parameters design about the main circuit of chopped wave cascade speed control system

Study about the current oscillating and harmonic analysis of high frequency chopped wave cascade speed control system

Notice of RetractionEnriched multiscale space in the boundary layers for problems with singular solution: Convergent on the coarse uniform grid

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Singularity detection method of chaotic time series using wavelet multi-resolution analysis

Single-fed single-patch broadband circularly polarized antenna for UHF RFID reader applications

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A new scheduling algorithm for server farms load balancing

Notice of RetractionReputation stretching in Chinese mutual fund families

A study of moving object detection based on combining background profile difference algorithm

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Study of text classification methods for data sets with huge features

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Notice of RetractionEssentialoils of Cinnamomum camphora wood and their antimicrobial activities

Notice of RetractionExtraction and determination of volatile constituents of wood from Cinnamomum camphora by Agilent-GC/MS

Notice of RetractionIdentification of important sections for emergency rescue road network

2009 International Conference on Industrial and Information Systems

Study of text classification methods for data sets with huge features

Content Provider	IEEE Xplore Digital Library
Author	Guiying Wei Xuedong Gao Sen Wu
Copyright Year	2010
Description	Author affiliation: School of Economics & Management, University of Science & Technology Beijing, China (Guiying Wei; Xuedong Gao; Sen Wu)
Abstract	Text classification has gained booming interest over the past few years. In this paper we look at the main approaches that have been taken towards text classification. The key text classification techniques including text model, feature selection methods and text classification algorithms are discussed .This work focus on the implementation of a text classification system based on Mutual Information and K-Nearest Neighbor algorithm and Support Vector Machine. The experimental results on Reuters collection are also presented. It shows that Mutual Information is a kind of efficient dimension reduction method for text data sets with huge features.
Starting Page	433
Ending Page	436
File Size	419132
Page Count	4
File Format	PDF
ISBN	9781424478606
e-ISBN	9781424478620
DOI	10.1109/INDUSIS.2010.5565817
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Feature selection Mutual Information K-Nearest Neighbor Indexing Text classification
Content Type	Text
Resource Type	Article

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