A Unified Fuzzy Data Model : Representation and Processing
A novel fuzzy data representation model which enables data mining with standard tools is introduced. Many data elements in the world are fuzzy in nature. There is an obvious need to represent and process such data effectively and efficiently, using the same standard tools for crisp data that are pop...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Gelbard, Roy [verfasserIn] Meged, Avichai [author] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2012 |
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| Schlagwörter: |
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| Umfang: |
Online-Ressource |
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| Reproduktion: |
IGI Global InfoSci Journals Archive 2000 - 2012 |
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| Übergeordnetes Werk: |
In: Journal of database management - Hershey, Pa : IGI Global, 2000, 23(2012), 1, Seite 78-102 |
| Übergeordnetes Werk: |
volume:23 ; year:2012 ; number:1 ; pages:78-102 |
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| DOI / URN: |
10.4018/jdm.2012010104 |
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NLEJ244519056 |
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| 520 | |a A novel fuzzy data representation model which enables data mining with standard tools is introduced. Many data elements in the world are fuzzy in nature. There is an obvious need to represent and process such data effectively and efficiently, using the same standard tools for crisp data that are popular with researchers and practitioners alike. Currently, however, standard tools cannot process or analyze data that are not adequately represented. The comprehensive data representation model put forward here extends principles of binary databases and provides a unified approach to all types of data: discrete and continuous, crisp and fuzzy. The model is illustrated on a baseline dataset and tested in clustering experiments matched against controlled groupings and a real dataset. The tests confirm that the implementation of the model not only enables the use of standard tools but also yields better results as regards segmentation and clustering of fuzzy datasets | ||
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A novel fuzzy data representation model which enables data mining with standard tools is introduced. Many data elements in the world are fuzzy in nature. There is an obvious need to represent and process such data effectively and efficiently, using the same standard tools for crisp data that are popular with researchers and practitioners alike. Currently, however, standard tools cannot process or analyze data that are not adequately represented. The comprehensive data representation model put forward here extends principles of binary databases and provides a unified approach to all types of data: discrete and continuous, crisp and fuzzy. The model is illustrated on a baseline dataset and tested in clustering experiments matched against controlled groupings and a real dataset. The tests confirm that the implementation of the model not only enables the use of standard tools but also yields better results as regards segmentation and clustering of fuzzy datasets |
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A novel fuzzy data representation model which enables data mining with standard tools is introduced. Many data elements in the world are fuzzy in nature. There is an obvious need to represent and process such data effectively and efficiently, using the same standard tools for crisp data that are popular with researchers and practitioners alike. Currently, however, standard tools cannot process or analyze data that are not adequately represented. The comprehensive data representation model put forward here extends principles of binary databases and provides a unified approach to all types of data: discrete and continuous, crisp and fuzzy. The model is illustrated on a baseline dataset and tested in clustering experiments matched against controlled groupings and a real dataset. The tests confirm that the implementation of the model not only enables the use of standard tools but also yields better results as regards segmentation and clustering of fuzzy datasets |
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A novel fuzzy data representation model which enables data mining with standard tools is introduced. Many data elements in the world are fuzzy in nature. There is an obvious need to represent and process such data effectively and efficiently, using the same standard tools for crisp data that are popular with researchers and practitioners alike. Currently, however, standard tools cannot process or analyze data that are not adequately represented. The comprehensive data representation model put forward here extends principles of binary databases and provides a unified approach to all types of data: discrete and continuous, crisp and fuzzy. The model is illustrated on a baseline dataset and tested in clustering experiments matched against controlled groupings and a real dataset. The tests confirm that the implementation of the model not only enables the use of standard tools but also yields better results as regards segmentation and clustering of fuzzy datasets |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">NLEJ244519056</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240202180314.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">150605s2012 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4018/jdm.2012010104</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)NLEJ244519056</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(VZGNL)10.4018/jdm.2012010104</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Gelbard, Roy</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A Unified Fuzzy Data Model</subfield><subfield code="b">Representation and Processing</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2012</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">A novel fuzzy data representation model which enables data mining with standard tools is introduced. 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