An Evaluation of the Usefulness of Case-Based Explanation
One of the perceived benefits of Case-Based Reasoning (CBR) is the potential to use retrieved cases to explain predictions. Surprisingly, this aspect of CBR has not been much researched. There has been some early work on knowledge-intensive approaches to CBR where the cases contain explanation patte...
Gespeichert in:
Hauptverfasser: | , , |
---|---|
Format: | Buchkapitel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 130 |
---|---|
container_issue | |
container_start_page | 122 |
container_title | |
container_volume | 2689 |
creator | Cunningham, Pádraig Doyle, Dónal Loughrey, John |
description | One of the perceived benefits of Case-Based Reasoning (CBR) is the potential to use retrieved cases to explain predictions. Surprisingly, this aspect of CBR has not been much researched. There has been some early work on knowledge-intensive approaches to CBR where the cases contain explanation patterns (e.g. SWALE). However, a more knowledge-light approach where the case similarity is the basis for explanation has received little attention. To explore this, we have developed a CBR system for predicting blood-alcohol level. We compare explanations of predictions produced by this system with alternative rule-based explanations. The case-based explanations fare very well in this evaluation and score significantly better than the rule-based alternative. |
doi_str_mv | 10.1007/3-540-45006-8_12 |
format | Book Chapter |
fullrecord | <record><control><sourceid>proquest_pasca</sourceid><recordid>TN_cdi_pascalfrancis_primary_15568405</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>EBC3071797_17_136</sourcerecordid><originalsourceid>FETCH-LOGICAL-c313t-358a4794225711c48587573d4e699904c94074ee7f10fc28ce7a3f9e2b8e90983</originalsourceid><addsrcrecordid>eNotUDtPwzAQNk8RSnfGLIwuZ58d22OpykOqxEJny3UdWghJiVME_x4n7el0J32v4SPklsGEAah7pFIAFRKgoNoyfkLGRmlM4ICxU5KxgjGKKMwZuR4IEIh4TjJA4NQogZckM1JLzgU3V2Qc4wekQc6U5Bkx0zqf_7hq77ptU-dNmXebkC9jKPdVHWLskZmLgT6ks87nv7vK1YP2hlyUrophfPwjsnycv82e6eL16WU2XVCPDDuKUjuhjOBcKsa80FIrqXAtQmGMAeGNACVCUCWD0nPtg3JYmsBXOhgwGkfk7pC7c9G7qmxd7bfR7trtl2v_LJOy0AJk0k0Oupio-j20dtU0n9EysH2ZFm2qxw7F2b7MZMBjcNt870PsbOgdPtRd6yq_cbsutNEiKKaMsiwtFvgPdeduyA</addsrcrecordid><sourcetype>Index Database</sourcetype><iscdi>true</iscdi><recordtype>book_chapter</recordtype><pqid>EBC3071797_17_136</pqid></control><display><type>book_chapter</type><title>An Evaluation of the Usefulness of Case-Based Explanation</title><source>Springer Books</source><creator>Cunningham, Pádraig ; Doyle, Dónal ; Loughrey, John</creator><contributor>Bridge, Derek ; Ashley, Kevin D ; Bridge, Derek G. ; Ashley, Kevin D.</contributor><creatorcontrib>Cunningham, Pádraig ; Doyle, Dónal ; Loughrey, John ; Bridge, Derek ; Ashley, Kevin D ; Bridge, Derek G. ; Ashley, Kevin D.</creatorcontrib><description>One of the perceived benefits of Case-Based Reasoning (CBR) is the potential to use retrieved cases to explain predictions. Surprisingly, this aspect of CBR has not been much researched. There has been some early work on knowledge-intensive approaches to CBR where the cases contain explanation patterns (e.g. SWALE). However, a more knowledge-light approach where the case similarity is the basis for explanation has received little attention. To explore this, we have developed a CBR system for predicting blood-alcohol level. We compare explanations of predictions produced by this system with alternative rule-based explanations. The case-based explanations fare very well in this evaluation and score significantly better than the rule-based alternative.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 3540404333</identifier><identifier>ISBN: 9783540404330</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 9783540450061</identifier><identifier>EISBN: 3540450068</identifier><identifier>DOI: 10.1007/3-540-45006-8_12</identifier><identifier>OCLC: 958522429</identifier><identifier>LCCallNum: Q334-342</identifier><language>eng</language><publisher>Germany: Springer Berlin / Heidelberg</publisher><subject>Applied sciences ; Artificial intelligence ; Blood Alcohol Content ; Computer science; control theory; systems ; Exact sciences and technology ; Explanation Pattern ; Intermediate Fact ; Learning and adaptive systems ; Medical Decision Support ; Target Case</subject><ispartof>Case-Based Reasoning Research and Development, 2003, Vol.2689, p.122-130</ispartof><rights>Springer-Verlag Berlin Heidelberg 2003</rights><rights>2004 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c313t-358a4794225711c48587573d4e699904c94074ee7f10fc28ce7a3f9e2b8e90983</citedby><relation>Lecture Notes in Computer Science</relation></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://ebookcentral.proquest.com/covers/3071797-l.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/3-540-45006-8_12$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/3-540-45006-8_12$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,777,778,782,787,788,791,4038,4039,27908,38238,41425,42494</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=15568405$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Bridge, Derek</contributor><contributor>Ashley, Kevin D</contributor><contributor>Bridge, Derek G.</contributor><contributor>Ashley, Kevin D.</contributor><creatorcontrib>Cunningham, Pádraig</creatorcontrib><creatorcontrib>Doyle, Dónal</creatorcontrib><creatorcontrib>Loughrey, John</creatorcontrib><title>An Evaluation of the Usefulness of Case-Based Explanation</title><title>Case-Based Reasoning Research and Development</title><description>One of the perceived benefits of Case-Based Reasoning (CBR) is the potential to use retrieved cases to explain predictions. Surprisingly, this aspect of CBR has not been much researched. There has been some early work on knowledge-intensive approaches to CBR where the cases contain explanation patterns (e.g. SWALE). However, a more knowledge-light approach where the case similarity is the basis for explanation has received little attention. To explore this, we have developed a CBR system for predicting blood-alcohol level. We compare explanations of predictions produced by this system with alternative rule-based explanations. The case-based explanations fare very well in this evaluation and score significantly better than the rule-based alternative.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Blood Alcohol Content</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Explanation Pattern</subject><subject>Intermediate Fact</subject><subject>Learning and adaptive systems</subject><subject>Medical Decision Support</subject><subject>Target Case</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>3540404333</isbn><isbn>9783540404330</isbn><isbn>9783540450061</isbn><isbn>3540450068</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2003</creationdate><recordtype>book_chapter</recordtype><recordid>eNotUDtPwzAQNk8RSnfGLIwuZ58d22OpykOqxEJny3UdWghJiVME_x4n7el0J32v4SPklsGEAah7pFIAFRKgoNoyfkLGRmlM4ICxU5KxgjGKKMwZuR4IEIh4TjJA4NQogZckM1JLzgU3V2Qc4wekQc6U5Bkx0zqf_7hq77ptU-dNmXebkC9jKPdVHWLskZmLgT6ks87nv7vK1YP2hlyUrophfPwjsnycv82e6eL16WU2XVCPDDuKUjuhjOBcKsa80FIrqXAtQmGMAeGNACVCUCWD0nPtg3JYmsBXOhgwGkfk7pC7c9G7qmxd7bfR7trtl2v_LJOy0AJk0k0Oupio-j20dtU0n9EysH2ZFm2qxw7F2b7MZMBjcNt870PsbOgdPtRd6yq_cbsutNEiKKaMsiwtFvgPdeduyA</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Cunningham, Pádraig</creator><creator>Doyle, Dónal</creator><creator>Loughrey, John</creator><general>Springer Berlin / Heidelberg</general><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>FFUUA</scope><scope>IQODW</scope></search><sort><creationdate>2003</creationdate><title>An Evaluation of the Usefulness of Case-Based Explanation</title><author>Cunningham, Pádraig ; Doyle, Dónal ; Loughrey, John</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c313t-358a4794225711c48587573d4e699904c94074ee7f10fc28ce7a3f9e2b8e90983</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Blood Alcohol Content</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Explanation Pattern</topic><topic>Intermediate Fact</topic><topic>Learning and adaptive systems</topic><topic>Medical Decision Support</topic><topic>Target Case</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cunningham, Pádraig</creatorcontrib><creatorcontrib>Doyle, Dónal</creatorcontrib><creatorcontrib>Loughrey, John</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cunningham, Pádraig</au><au>Doyle, Dónal</au><au>Loughrey, John</au><au>Bridge, Derek</au><au>Ashley, Kevin D</au><au>Bridge, Derek G.</au><au>Ashley, Kevin D.</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>An Evaluation of the Usefulness of Case-Based Explanation</atitle><btitle>Case-Based Reasoning Research and Development</btitle><seriestitle>Lecture Notes in Computer Science</seriestitle><date>2003</date><risdate>2003</risdate><volume>2689</volume><spage>122</spage><epage>130</epage><pages>122-130</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>3540404333</isbn><isbn>9783540404330</isbn><eisbn>9783540450061</eisbn><eisbn>3540450068</eisbn><abstract>One of the perceived benefits of Case-Based Reasoning (CBR) is the potential to use retrieved cases to explain predictions. Surprisingly, this aspect of CBR has not been much researched. There has been some early work on knowledge-intensive approaches to CBR where the cases contain explanation patterns (e.g. SWALE). However, a more knowledge-light approach where the case similarity is the basis for explanation has received little attention. To explore this, we have developed a CBR system for predicting blood-alcohol level. We compare explanations of predictions produced by this system with alternative rule-based explanations. The case-based explanations fare very well in this evaluation and score significantly better than the rule-based alternative.</abstract><cop>Germany</cop><pub>Springer Berlin / Heidelberg</pub><doi>10.1007/3-540-45006-8_12</doi><oclcid>958522429</oclcid><tpages>9</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0302-9743 |
ispartof | Case-Based Reasoning Research and Development, 2003, Vol.2689, p.122-130 |
issn | 0302-9743 1611-3349 |
language | eng |
recordid | cdi_pascalfrancis_primary_15568405 |
source | Springer Books |
subjects | Applied sciences Artificial intelligence Blood Alcohol Content Computer science control theory systems Exact sciences and technology Explanation Pattern Intermediate Fact Learning and adaptive systems Medical Decision Support Target Case |
title | An Evaluation of the Usefulness of Case-Based Explanation |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T02%3A05%3A53IST&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:book&rft.genre=bookitem&rft.atitle=An%20Evaluation%20of%20the%20Usefulness%20of%20Case-Based%20Explanation&rft.btitle=Case-Based%20Reasoning%20Research%20and%20Development&rft.au=Cunningham,%20P%C3%A1draig&rft.date=2003&rft.volume=2689&rft.spage=122&rft.epage=130&rft.pages=122-130&rft.issn=0302-9743&rft.eissn=1611-3349&rft.isbn=3540404333&rft.isbn_list=9783540404330&rft_id=info:doi/10.1007/3-540-45006-8_12&rft_dat=%3Cproquest_pasca%3EEBC3071797_17_136%3C/proquest_pasca%3E%3Curl%3E%3C/url%3E&rft.eisbn=9783540450061&rft.eisbn_list=3540450068&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=EBC3071797_17_136&rft_id=info:pmid/&rfr_iscdi=true |