### Abstract

Though the data integration problem of relational databases has been well studied, little work addresses the problem In the context of fuzzy relational databases. The fuzzy relational model relies on the specification of either a similarity relation or a proximity relation for each scalar domain in the fuzzy database. Without the constraint of max-min transitivity, proximity relations can be defined in an intuitive way. This paper states a resolution in integrating multiple proximity relations. First, the closure property of weighted combination of multiple proximity relations is shown. Then, the notion of consistency constraint is defined. It has been proved that the weighted combination of proximity relations under such constrain Is still consistent with each of the proximity relations prior to their integration.

Original language | English |
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Title of host publication | Proceedings of the International Conference on Information and Knowledge Engineering |

Editors | N. Goharian, N. Goharian |

Pages | 182-185 |

Number of pages | 4 |

Volume | 1 |

Publication status | Published - 2003 |

Externally published | Yes |

Event | Proceedings of the International Conference on Information and Knowledge Engineering 2003 - Las Vegas, NV, United States Duration: Jun 23 2003 → Jun 26 2003 |

### Other

Other | Proceedings of the International Conference on Information and Knowledge Engineering 2003 |
---|---|

Country | United States |

City | Las Vegas, NV |

Period | 6/23/03 → 6/26/03 |

### Fingerprint

### Keywords

- Data integration
- Fuzzy databases
- Proximity relations
- Similarity relations

### ASJC Scopus subject areas

- Library and Information Sciences
- Information Systems

### Cite this

*Proceedings of the International Conference on Information and Knowledge Engineering*(Vol. 1, pp. 182-185)

**Integration of proximity relations under consistency constraint.** / Liu, Yu Chih; Chang, Tsu Hao; Lin, Jun Lin.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the International Conference on Information and Knowledge Engineering.*vol. 1, pp. 182-185, Proceedings of the International Conference on Information and Knowledge Engineering 2003, Las Vegas, NV, United States, 6/23/03.

}

TY - GEN

T1 - Integration of proximity relations under consistency constraint

AU - Liu, Yu Chih

AU - Chang, Tsu Hao

AU - Lin, Jun Lin

PY - 2003

Y1 - 2003

N2 - Though the data integration problem of relational databases has been well studied, little work addresses the problem In the context of fuzzy relational databases. The fuzzy relational model relies on the specification of either a similarity relation or a proximity relation for each scalar domain in the fuzzy database. Without the constraint of max-min transitivity, proximity relations can be defined in an intuitive way. This paper states a resolution in integrating multiple proximity relations. First, the closure property of weighted combination of multiple proximity relations is shown. Then, the notion of consistency constraint is defined. It has been proved that the weighted combination of proximity relations under such constrain Is still consistent with each of the proximity relations prior to their integration.

AB - Though the data integration problem of relational databases has been well studied, little work addresses the problem In the context of fuzzy relational databases. The fuzzy relational model relies on the specification of either a similarity relation or a proximity relation for each scalar domain in the fuzzy database. Without the constraint of max-min transitivity, proximity relations can be defined in an intuitive way. This paper states a resolution in integrating multiple proximity relations. First, the closure property of weighted combination of multiple proximity relations is shown. Then, the notion of consistency constraint is defined. It has been proved that the weighted combination of proximity relations under such constrain Is still consistent with each of the proximity relations prior to their integration.

KW - Data integration

KW - Fuzzy databases

KW - Proximity relations

KW - Similarity relations

UR - http://www.scopus.com/inward/record.url?scp=1642341083&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=1642341083&partnerID=8YFLogxK

M3 - Conference contribution

SN - 1932415076

VL - 1

SP - 182

EP - 185

BT - Proceedings of the International Conference on Information and Knowledge Engineering

A2 - Goharian, N.

A2 - Goharian, N.

ER -