A maximum entropy approach to natural language processing

A maximum entropy approach to natural language processing

The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper, we de...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computational linguistics - Association for Computational Linguistics 1996-03, Vol.22 (1), p.39-71
Hauptverfasser: BERGER, A. L, DELLA PIETRA, V. J, DELLA PIETRA, S. A
Format: Artikel
Sprache:eng
Schlagworte:
Applied linguistics
Computational linguistics
Linguistics
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 71
container_issue 1
container_start_page 39
container_title Computational linguistics - Association for Computational Linguistics
container_volume 22
creator BERGER, A. L
DELLA PIETRA, V. J
DELLA PIETRA, S. A
description The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper, we describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.
format Article
fullrecord <record><control><sourceid>proquest_pasca</sourceid><recordid>TN_cdi_proquest_miscellaneous_58320210</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>58320210</sourcerecordid><originalsourceid>FETCH-LOGICAL-p244t-d75f0a960e199b772592652db7bfb8258f230af4289b88251be2aff0ded9ee0c3</originalsourceid><addsrcrecordid>eNqFjk1LxDAYhIMouK7-hxzEW-HNm2aTHJfFL1jwoufyNk1qpV8mLbj_3oB79zQM8zAzF2wjlITCSoGXbAPGigJB6Gt2k9IXAGiQesPsng_00w3rwP24xGk-cZrnOJH75MvER1rWSD3vaWxXaj3PkfMpdWN7y64C9cnfnXXLPp4e3w8vxfHt-fWwPxYzluVSNFoFILsDL6yttUZlcaewqXUdaoPKBJRAoURja5O9qD1SCND4xnoPTm7Zw19vnv5efVqqoUvO9_mSn9ZUKSMRUMC_INo8AgYzeH8GKTnqQ6TRdamaYzdQPFUSjdQZ-wWNol-g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>29428082</pqid></control><display><type>article</type><title>A maximum entropy approach to natural language processing</title><source>Alma/SFX Local Collection</source><creator>BERGER, A. L ; DELLA PIETRA, V. J ; DELLA PIETRA, S. A</creator><creatorcontrib>BERGER, A. L ; DELLA PIETRA, V. J ; DELLA PIETRA, S. A</creatorcontrib><description>The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper, we describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.</description><identifier>ISSN: 0891-2017</identifier><identifier>EISSN: 1530-9312</identifier><identifier>CODEN: AJCLD9</identifier><language>eng</language><publisher>Cambridge, MA: MIT Press</publisher><subject>Applied linguistics ; Computational linguistics ; Linguistics</subject><ispartof>Computational linguistics - Association for Computational Linguistics, 1996-03, Vol.22 (1), p.39-71</ispartof><rights>1996 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=3283782$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>BERGER, A. L</creatorcontrib><creatorcontrib>DELLA PIETRA, V. J</creatorcontrib><creatorcontrib>DELLA PIETRA, S. A</creatorcontrib><title>A maximum entropy approach to natural language processing</title><title>Computational linguistics - Association for Computational Linguistics</title><description>The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper, we describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.</description><subject>Applied linguistics</subject><subject>Computational linguistics</subject><subject>Linguistics</subject><issn>0891-2017</issn><issn>1530-9312</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1996</creationdate><recordtype>article</recordtype><recordid>eNqFjk1LxDAYhIMouK7-hxzEW-HNm2aTHJfFL1jwoufyNk1qpV8mLbj_3oB79zQM8zAzF2wjlITCSoGXbAPGigJB6Gt2k9IXAGiQesPsng_00w3rwP24xGk-cZrnOJH75MvER1rWSD3vaWxXaj3PkfMpdWN7y64C9cnfnXXLPp4e3w8vxfHt-fWwPxYzluVSNFoFILsDL6yttUZlcaewqXUdaoPKBJRAoURja5O9qD1SCND4xnoPTm7Zw19vnv5efVqqoUvO9_mSn9ZUKSMRUMC_INo8AgYzeH8GKTnqQ6TRdamaYzdQPFUSjdQZ-wWNol-g</recordid><startdate>19960301</startdate><enddate>19960301</enddate><creator>BERGER, A. L</creator><creator>DELLA PIETRA, V. J</creator><creator>DELLA PIETRA, S. A</creator><general>MIT Press</general><scope>IQODW</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7T9</scope></search><sort><creationdate>19960301</creationdate><title>A maximum entropy approach to natural language processing</title><author>BERGER, A. L ; DELLA PIETRA, V. J ; DELLA PIETRA, S. A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p244t-d75f0a960e199b772592652db7bfb8258f230af4289b88251be2aff0ded9ee0c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Applied linguistics</topic><topic>Computational linguistics</topic><topic>Linguistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>BERGER, A. L</creatorcontrib><creatorcontrib>DELLA PIETRA, V. J</creatorcontrib><creatorcontrib>DELLA PIETRA, S. A</creatorcontrib><collection>Pascal-Francis</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Linguistics and Language Behavior Abstracts (LLBA)</collection><jtitle>Computational linguistics - Association for Computational Linguistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>BERGER, A. L</au><au>DELLA PIETRA, V. J</au><au>DELLA PIETRA, S. A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A maximum entropy approach to natural language processing</atitle><jtitle>Computational linguistics - Association for Computational Linguistics</jtitle><date>1996-03-01</date><risdate>1996</risdate><volume>22</volume><issue>1</issue><spage>39</spage><epage>71</epage><pages>39-71</pages><issn>0891-2017</issn><eissn>1530-9312</eissn><coden>AJCLD9</coden><abstract>The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper, we describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.</abstract><cop>Cambridge, MA</cop><pub>MIT Press</pub><tpages>33</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0891-2017
ispartof Computational linguistics - Association for Computational Linguistics, 1996-03, Vol.22 (1), p.39-71
issn 0891-2017
1530-9312
language eng
recordid cdi_proquest_miscellaneous_58320210
source Alma/SFX Local Collection
subjects Applied linguistics
Computational linguistics
Linguistics
title A maximum entropy approach to natural language processing
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T09%3A30%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pasca&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20maximum%20entropy%20approach%20to%20natural%20language%20processing&rft.jtitle=Computational%20linguistics%20-%20Association%20for%20Computational%20Linguistics&rft.au=BERGER,%20A.%20L&rft.date=1996-03-01&rft.volume=22&rft.issue=1&rft.spage=39&rft.epage=71&rft.pages=39-71&rft.issn=0891-2017&rft.eissn=1530-9312&rft.coden=AJCLD9&rft_id=info:doi/&rft_dat=%3Cproquest_pasca%3E58320210%3C/proquest_pasca%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=29428082&rft_id=info:pmid/&rfr_iscdi=true