A Flexible Fuzzy Expert System for Fuzzy Duplicate Elimination in Data Cleaning

Data cleaning deals with the detection and removal of errors and inconsistencies in data, gathered from distributed sources. This process is essential for drawing correct conclusions from data in decision support systems. Eliminating fuzzy duplicate records is a fundamental part of the data cleaning...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Shahri, Hamid Haidarian, Barforush, Ahmad Abdollahzadeh
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 170
container_issue
container_start_page 161
container_title
container_volume
creator Shahri, Hamid Haidarian
Barforush, Ahmad Abdollahzadeh
description Data cleaning deals with the detection and removal of errors and inconsistencies in data, gathered from distributed sources. This process is essential for drawing correct conclusions from data in decision support systems. Eliminating fuzzy duplicate records is a fundamental part of the data cleaning process. The vagueness and uncertainty involved in detecting fuzzy duplicates make it a niche, for applying fuzzy reasoning. Although uncertainty alg ebras like fuzzy logic are known, their applicability to the problem of duplicate elimination has remained unexplored and unclear, until today. In this paper, a novel and flexible fuzzy expert system for detection and elimination of fuzzy duplicates in the process of data cleaning is devised, which circumvents the repetitive and inconvenient task of hard-coding. Some of the crucial advantages of this approach are its flexibility, ease of use, extendibility, fast development time and efficient run time, when used in various information systems.
doi_str_mv 10.1007/978-3-540-30075-5_16
format Conference Proceeding
fullrecord <record><control><sourceid>pascalfrancis_sprin</sourceid><recordid>TN_cdi_pascalfrancis_primary_16164049</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>16164049</sourcerecordid><originalsourceid>FETCH-LOGICAL-p228t-973649751d9146a0ae33b090470d34f3f703345c7975688ba2148d04e6739a0d3</originalsourceid><addsrcrecordid>eNotkMtuwyAQRelLaprmD7pg0yXt4MFgllEebaVIWbRdI-zgiNaxLeNISb4-5DEbNPceITiEvHB44wDqXauMIUsFMIxrylLD5Q15wpicA31LBlxyzhCFviOjyJ-6JNEo4Z4MIpUwrQQ-klEIfxCHYwpZNiDLMZ1XbufzytH59nDY09mudV1Pv_ehdxtaNt01n27byhe2d3RW-Y2vbe-bmvqaTm1v6aRytvb1-pk8lLYKbnQ9h-R3PvuZfLLF8uNrMl6wNkmyPj4GpdAq5SvNhbRgHWIOGoSCFYoSSwXxL2mhIiOzLLcJF9kKhJMKtY3MkLxe7m1tKGxVdrYufDBt5ze220c_XAoQOnLJhQuxqteuM3nT_AfDwZzUmqjKoImyzNmkOanFI8B3ZL8</addsrcrecordid><sourcetype>Index Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>A Flexible Fuzzy Expert System for Fuzzy Duplicate Elimination in Data Cleaning</title><source>Springer Books</source><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Shahri, Hamid Haidarian ; Barforush, Ahmad Abdollahzadeh</creator><contributor>Galindo, Fernando ; Takizawa, Makoto ; Traunmüller, Roland</contributor><creatorcontrib>Shahri, Hamid Haidarian ; Barforush, Ahmad Abdollahzadeh ; Galindo, Fernando ; Takizawa, Makoto ; Traunmüller, Roland</creatorcontrib><description>Data cleaning deals with the detection and removal of errors and inconsistencies in data, gathered from distributed sources. This process is essential for drawing correct conclusions from data in decision support systems. Eliminating fuzzy duplicate records is a fundamental part of the data cleaning process. The vagueness and uncertainty involved in detecting fuzzy duplicates make it a niche, for applying fuzzy reasoning. Although uncertainty alg ebras like fuzzy logic are known, their applicability to the problem of duplicate elimination has remained unexplored and unclear, until today. In this paper, a novel and flexible fuzzy expert system for detection and elimination of fuzzy duplicates in the process of data cleaning is devised, which circumvents the repetitive and inconvenient task of hard-coding. Some of the crucial advantages of this approach are its flexibility, ease of use, extendibility, fast development time and efficient run time, when used in various information systems.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540229360</identifier><identifier>ISBN: 3540229361</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 3540300759</identifier><identifier>EISBN: 9783540300755</identifier><identifier>DOI: 10.1007/978-3-540-30075-5_16</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>Applied sciences ; Computer science; control theory; systems ; Exact sciences and technology ; Fuzzy Rule ; Fuzzy Subset ; Inference Process ; Information systems. Data bases ; Linguistic Term ; Membership Function ; Memory organisation. Data processing ; Software</subject><ispartof>Database and Expert Systems Applications, 2004, p.161-170</ispartof><rights>Springer-Verlag Berlin Heidelberg 2004</rights><rights>2004 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/978-3-540-30075-5_16$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/978-3-540-30075-5_16$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,779,780,784,789,790,793,4050,4051,27925,38255,41442,42511</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=16164049$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Galindo, Fernando</contributor><contributor>Takizawa, Makoto</contributor><contributor>Traunmüller, Roland</contributor><creatorcontrib>Shahri, Hamid Haidarian</creatorcontrib><creatorcontrib>Barforush, Ahmad Abdollahzadeh</creatorcontrib><title>A Flexible Fuzzy Expert System for Fuzzy Duplicate Elimination in Data Cleaning</title><title>Database and Expert Systems Applications</title><description>Data cleaning deals with the detection and removal of errors and inconsistencies in data, gathered from distributed sources. This process is essential for drawing correct conclusions from data in decision support systems. Eliminating fuzzy duplicate records is a fundamental part of the data cleaning process. The vagueness and uncertainty involved in detecting fuzzy duplicates make it a niche, for applying fuzzy reasoning. Although uncertainty alg ebras like fuzzy logic are known, their applicability to the problem of duplicate elimination has remained unexplored and unclear, until today. In this paper, a novel and flexible fuzzy expert system for detection and elimination of fuzzy duplicates in the process of data cleaning is devised, which circumvents the repetitive and inconvenient task of hard-coding. Some of the crucial advantages of this approach are its flexibility, ease of use, extendibility, fast development time and efficient run time, when used in various information systems.</description><subject>Applied sciences</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Fuzzy Rule</subject><subject>Fuzzy Subset</subject><subject>Inference Process</subject><subject>Information systems. Data bases</subject><subject>Linguistic Term</subject><subject>Membership Function</subject><subject>Memory organisation. Data processing</subject><subject>Software</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540229360</isbn><isbn>3540229361</isbn><isbn>3540300759</isbn><isbn>9783540300755</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotkMtuwyAQRelLaprmD7pg0yXt4MFgllEebaVIWbRdI-zgiNaxLeNISb4-5DEbNPceITiEvHB44wDqXauMIUsFMIxrylLD5Q15wpicA31LBlxyzhCFviOjyJ-6JNEo4Z4MIpUwrQQ-klEIfxCHYwpZNiDLMZ1XbufzytH59nDY09mudV1Pv_ehdxtaNt01n27byhe2d3RW-Y2vbe-bmvqaTm1v6aRytvb1-pk8lLYKbnQ9h-R3PvuZfLLF8uNrMl6wNkmyPj4GpdAq5SvNhbRgHWIOGoSCFYoSSwXxL2mhIiOzLLcJF9kKhJMKtY3MkLxe7m1tKGxVdrYufDBt5ze220c_XAoQOnLJhQuxqteuM3nT_AfDwZzUmqjKoImyzNmkOanFI8B3ZL8</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Shahri, Hamid Haidarian</creator><creator>Barforush, Ahmad Abdollahzadeh</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2004</creationdate><title>A Flexible Fuzzy Expert System for Fuzzy Duplicate Elimination in Data Cleaning</title><author>Shahri, Hamid Haidarian ; Barforush, Ahmad Abdollahzadeh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p228t-973649751d9146a0ae33b090470d34f3f703345c7975688ba2148d04e6739a0d3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Applied sciences</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Fuzzy Rule</topic><topic>Fuzzy Subset</topic><topic>Inference Process</topic><topic>Information systems. Data bases</topic><topic>Linguistic Term</topic><topic>Membership Function</topic><topic>Memory organisation. Data processing</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shahri, Hamid Haidarian</creatorcontrib><creatorcontrib>Barforush, Ahmad Abdollahzadeh</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shahri, Hamid Haidarian</au><au>Barforush, Ahmad Abdollahzadeh</au><au>Galindo, Fernando</au><au>Takizawa, Makoto</au><au>Traunmüller, Roland</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A Flexible Fuzzy Expert System for Fuzzy Duplicate Elimination in Data Cleaning</atitle><btitle>Database and Expert Systems Applications</btitle><date>2004</date><risdate>2004</risdate><spage>161</spage><epage>170</epage><pages>161-170</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540229360</isbn><isbn>3540229361</isbn><eisbn>3540300759</eisbn><eisbn>9783540300755</eisbn><abstract>Data cleaning deals with the detection and removal of errors and inconsistencies in data, gathered from distributed sources. This process is essential for drawing correct conclusions from data in decision support systems. Eliminating fuzzy duplicate records is a fundamental part of the data cleaning process. The vagueness and uncertainty involved in detecting fuzzy duplicates make it a niche, for applying fuzzy reasoning. Although uncertainty alg ebras like fuzzy logic are known, their applicability to the problem of duplicate elimination has remained unexplored and unclear, until today. In this paper, a novel and flexible fuzzy expert system for detection and elimination of fuzzy duplicates in the process of data cleaning is devised, which circumvents the repetitive and inconvenient task of hard-coding. Some of the crucial advantages of this approach are its flexibility, ease of use, extendibility, fast development time and efficient run time, when used in various information systems.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/978-3-540-30075-5_16</doi><tpages>10</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0302-9743
ispartof Database and Expert Systems Applications, 2004, p.161-170
issn 0302-9743
1611-3349
language eng
recordid cdi_pascalfrancis_primary_16164049
source Springer Books; IEEE Electronic Library (IEL) Conference Proceedings
subjects Applied sciences
Computer science
control theory
systems
Exact sciences and technology
Fuzzy Rule
Fuzzy Subset
Inference Process
Information systems. Data bases
Linguistic Term
Membership Function
Memory organisation. Data processing
Software
title A Flexible Fuzzy Expert System for Fuzzy Duplicate Elimination in Data Cleaning
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T11%3A13%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-pascalfrancis_sprin&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=A%20Flexible%20Fuzzy%20Expert%20System%20for%20Fuzzy%20Duplicate%20Elimination%20in%20Data%20Cleaning&rft.btitle=Database%20and%20Expert%20Systems%20Applications&rft.au=Shahri,%20Hamid%20Haidarian&rft.date=2004&rft.spage=161&rft.epage=170&rft.pages=161-170&rft.issn=0302-9743&rft.eissn=1611-3349&rft.isbn=9783540229360&rft.isbn_list=3540229361&rft_id=info:doi/10.1007/978-3-540-30075-5_16&rft_dat=%3Cpascalfrancis_sprin%3E16164049%3C/pascalfrancis_sprin%3E%3Curl%3E%3C/url%3E&rft.eisbn=3540300759&rft.eisbn_list=9783540300755&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true