An Experimental Agricultural Data Mining System
Identifieur interne : 000022 ( Istex/Corpus ); précédent : 000021; suivant : 000023An Experimental Agricultural Data Mining System
Auteurs : Kazunori MatsumotoSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 1998.
Abstract
Abstract: Agriculture is an information-intensive industry from an essential point of view. Many factors such as soil, fertilizer, temperature, precipitation, sunray, etc. are all affect harvest, so that information about them is carefully investigated by expert persons in deciding agricultural activities. We thus expect to build an intelligent agricultural information system to assist the experts and to help an improvement on agricultural technologies [7]. Towards this purpose, we firstly need to provide a system which can reveal hidden relations among agricultural factors. Although traditional statistical methods have already applied to this field, we expect recent data mining technologies to bring still more fruitful results. In particular, an expert can easily examines IF - THEN style rules extracted by the typical data mining methods [1],[6], he then may give further investigations around the rules with existing knowledge
Url:
DOI: 10.1007/3-540-49292-5_60
Links to Exploration step
ISTEX:15024CECE2C83663B093864019879575792A1D5ELe document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct:series"><teiHeader><fileDesc><titleStmt><title xml:lang="en">An Experimental Agricultural Data Mining System</title><author><name sortKey="Matsumoto, Kazunori" sort="Matsumoto, Kazunori" uniqKey="Matsumoto K" first="Kazunori" last="Matsumoto">Kazunori Matsumoto</name><affiliation><mods:affiliation>System Integration Technology Center, Toshiba Corp, USA</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: kazunori@sitc.toshiba.co.jp</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:15024CECE2C83663B093864019879575792A1D5E</idno><date when="1998" year="1998">1998</date><idno type="doi">10.1007/3-540-49292-5_60</idno><idno type="url">https://api.istex.fr/document/15024CECE2C83663B093864019879575792A1D5E/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000022</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000022</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">An Experimental Agricultural Data Mining System</title><author><name sortKey="Matsumoto, Kazunori" sort="Matsumoto, Kazunori" uniqKey="Matsumoto K" first="Kazunori" last="Matsumoto">Kazunori Matsumoto</name><affiliation><mods:affiliation>System Integration Technology Center, Toshiba Corp, USA</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: kazunori@sitc.toshiba.co.jp</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>1998</date></imprint><idno type="ISSN">0302-9743</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">15024CECE2C83663B093864019879575792A1D5E</idno><idno type="DOI">10.1007/3-540-49292-5_60</idno><idno type="ChapterID">60</idno><idno type="ChapterID">Chap60</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: Agriculture is an information-intensive industry from an essential point of view. Many factors such as soil, fertilizer, temperature, precipitation, sunray, etc. are all affect harvest, so that information about them is carefully investigated by expert persons in deciding agricultural activities. We thus expect to build an intelligent agricultural information system to assist the experts and to help an improvement on agricultural technologies [7]. Towards this purpose, we firstly need to provide a system which can reveal hidden relations among agricultural factors. Although traditional statistical methods have already applied to this field, we expect recent data mining technologies to bring still more fruitful results. In particular, an expert can easily examines IF - THEN style rules extracted by the typical data mining methods [1],[6], he then may give further investigations around the rules with existing knowledge</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Kazunori Matsumoto</name><affiliations><json:string>System Integration Technology Center, Toshiba Corp, USA</json:string><json:string>E-mail: kazunori@sitc.toshiba.co.jp</json:string></affiliations></json:item></author><language><json:string>eng</json:string></language><originalGenre><json:string>OriginalPaper</json:string></originalGenre><abstract>Abstract: Agriculture is an information-intensive industry from an essential point of view. Many factors such as soil, fertilizer, temperature, precipitation, sunray, etc. are all affect harvest, so that information about them is carefully investigated by expert persons in deciding agricultural activities. We thus expect to build an intelligent agricultural information system to assist the experts and to help an improvement on agricultural technologies [7]. Towards this purpose, we firstly need to provide a system which can reveal hidden relations among agricultural factors. Although traditional statistical methods have already applied to this field, we expect recent data mining technologies to bring still more fruitful results. 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Many factors such as soil, fertilizer, temperature, precipitation, sunray, etc. are all affect harvest, so that information about them is carefully investigated by expert persons in deciding agricultural activities. We thus expect to build an intelligent agricultural information system to assist the experts and to help an improvement on agricultural technologies [7]. Towards this purpose, we firstly need to provide a system which can reveal hidden relations among agricultural factors. Although traditional statistical methods have already applied to this field, we expect recent data mining technologies to bring still more fruitful results. In particular, an expert can easily examines IF - THEN style rules extracted by the typical data mining methods [1],[6], he then may give further investigations around the rules with existing knowledge</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Book><SubSeries><SubSeriesInfo><SubSeriesID>1244</SubSeriesID><SubSeriesTitle Language="En">Lecture Notes in Artificial Intelligence</SubSeriesTitle><SubSeriesSubTitle Language="En">Subseries of Lecture Notes in Computer Science</SubSeriesSubTitle></SubSeriesInfo><SubSeriesHeader><EditorGroup><Editor AffiliationIDS="Aff3"><EditorName DisplayOrder="Western"><GivenName>Jaime</GivenName><GivenName>G.</GivenName><FamilyName>Carbonell</FamilyName></EditorName></Editor><Editor AffiliationIDS="Aff4"><EditorName DisplayOrder="Western"><GivenName>Jörg</GivenName><FamilyName>Siekmann</FamilyName></EditorName></Editor><Affiliation ID="Aff3"><OrgName>Carnegie Mellon University</OrgName><OrgAddress><City>Pittsburgh</City><State>PA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff4"><OrgName>University of Saarland</OrgName><OrgAddress><City>Saarbrücken</City><Country>Germany</Country></OrgAddress></Affiliation></EditorGroup></SubSeriesHeader></SubSeries></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>An Experimental Agricultural Data Mining System</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>An Experimental Agricultural Data Mining System</title></titleInfo><name type="personal"><namePart type="given">Kazunori</namePart><namePart type="family">Matsumoto</namePart><affiliation>System Integration Technology Center, Toshiba Corp, USA</affiliation><affiliation>E-mail: kazunori@sitc.toshiba.co.jp</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2003-01-14</dateIssued><copyrightDate encoding="w3cdtf">1998</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: Agriculture is an information-intensive industry from an essential point of view. Many factors such as soil, fertilizer, temperature, precipitation, sunray, etc. are all affect harvest, so that information about them is carefully investigated by expert persons in deciding agricultural activities. We thus expect to build an intelligent agricultural information system to assist the experts and to help an improvement on agricultural technologies [7]. Towards this purpose, we firstly need to provide a system which can reveal hidden relations among agricultural factors. Although traditional statistical methods have already applied to this field, we expect recent data mining technologies to bring still more fruitful results. In particular, an expert can easily examines IF - THEN style rules extracted by the typical data mining methods [1],[6], he then may give further investigations around the rules with existing knowledge</abstract><relatedItem type="host"><titleInfo><title>Discovey Science</title><subTitle>First International Conference, DS’98 Fukuoka, Japan, December 14–16, 1998 Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Setsuo</namePart><namePart type="family">Arikawa</namePart><affiliation>Department of Informatics, Kyushu University, 812-8581, Fukuoka, USA</affiliation><affiliation>E-mail: arikawa@i.kyushu-u.ac.jp</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Hiroshi</namePart><namePart type="family">Motoda</namePart><affiliation>Institute of Scientific and Industrial Research Devision of Intelligent Systems Science, Osaka University, 567-0047, 8-1 Mihogaoka, Ibaraki, Osaka, Japan</affiliation><affiliation>E-mail: motoda@sanken.osaka-u.ac.jp</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="book-series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">1998</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book-Subject-Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book-Subject-Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. Robotics)</topic><topic authority="SpringerSubjectCodes" authorityURI="I18024">Database Management</topic><topic authority="SpringerSubjectCodes" authorityURI="I18032">Information Storage and Retrieval</topic><topic authority="SpringerSubjectCodes" authorityURI="W26007">Business Information Systems</topic><topic authority="SpringerSubjectCodes" authorityURI="T11022">Systems and Information Theory in Engineering</topic></subject><identifier type="DOI">10.1007/3-540-49292-5</identifier><identifier type="ISBN">978-3-540-65390-5</identifier><identifier type="eISBN">978-3-540-49292-4</identifier><identifier type="ISSN">0302-9743</identifier><identifier type="BookTitleID">59051</identifier><identifier type="BookID">3-540-49292-5</identifier><identifier type="BookChapterCount">67</identifier><identifier type="BookVolumeNumber">1532</identifier><identifier type="BookSequenceNumber">1532</identifier><part><date>1998</date><detail type="volume"><number>1532</number><caption>vol.</caption></detail><extent unit="pages"><start>439</start><end>440</end></extent></part><recordInfo><recordOrigin>Springer-Verlag Berlin Heidelberg, 1998</recordOrigin></recordInfo></relatedItem><relatedItem type="series"><titleInfo><title>Lecture Notes in Computer Science</title></titleInfo><name type="personal"><namePart type="given">G.</namePart><namePart type="family">Goos</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">J.</namePart><namePart type="family">Hartmanis</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">J.</namePart><namePart type="family">van Leeuwen</namePart><role><roleTerm type="text">editor</roleTerm></role></name><originInfo><copyrightDate encoding="w3cdtf">1998</copyrightDate><issuance>serial</issuance></originInfo><relatedItem type="constituent"><titleInfo><title>Lecture Notes in Artificial Intelligence</title><subTitle>Subseries of Lecture Notes in Computer Science</subTitle></titleInfo><name type="personal"><namePart type="given">G.</namePart><namePart type="family">Goos</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">J.</namePart><namePart type="family">Hartmanis</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">J.</namePart><namePart type="family">van Leeuwen</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Setsuo</namePart><namePart type="family">Arikawa</namePart><affiliation>Department of Informatics, Kyushu University, 812-8581, Fukuoka, USA</affiliation><affiliation>E-mail: arikawa@i.kyushu-u.ac.jp</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Hiroshi</namePart><namePart type="family">Motoda</namePart><affiliation>Institute of Scientific and Industrial Research Devision of Intelligent Systems Science, Osaka University, 567-0047, 8-1 Mihogaoka, Ibaraki, Osaka, Japan</affiliation><affiliation>E-mail: motoda@sanken.osaka-u.ac.jp</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jaime</namePart><namePart type="given">G.</namePart><namePart type="family">Carbonell</namePart><affiliation>Carnegie Mellon University, Pittsburgh, PA, USA</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jörg</namePart><namePart type="family">Siekmann</namePart><affiliation>University of Saarland, Saarbrücken, Germany</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="sub-series"></genre><identifier type="SubSeriesID">1244</identifier></relatedItem><identifier type="ISSN">0302-9743</identifier><identifier type="SeriesID">558</identifier><recordInfo><recordOrigin>Springer-Verlag Berlin Heidelberg, 1998</recordOrigin></recordInfo></relatedItem><identifier type="istex">15024CECE2C83663B093864019879575792A1D5E</identifier><identifier type="DOI">10.1007/3-540-49292-5_60</identifier><identifier type="ChapterID">60</identifier><identifier type="ChapterID">Chap60</identifier><accessCondition type="use and reproduction" contentType="copyright">Springer-Verlag Berlin Heidelberg, 1998</accessCondition><recordInfo><recordContentSource>SPRINGER</recordContentSource><recordOrigin>Springer-Verlag Berlin Heidelberg, 1998</recordOrigin></recordInfo></mods></metadata></istex></record>Pour manipuler ce document sous Unix (Dilib)
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