Paper Info
Title
A Data Model for Flexible Querying
Abstract
The paper is dealing with the problem of flexible querying using vague linguistic expressions and user dependent requirements. We propose a solution based on incorporating weights into scoring rules by the usage of fuzzy logic and fuzzy similarities. We define a data model, which enables to answer queries over crisp data using fuzzy knowledge base, fuzzy interpretation of vague expressions and fuzzy similarities. We present an extension of a positive relational algebra and show that its the expressive power together with a fuzzy fixpoint operator is sufficient for evaluating fuzzy Datalog programs. We discuss also a computational model for queries with a threshold on truth values and optimization of such queries.
Year
DOI
Venue
2001
10.1007/3-540-44803-9_22
ADBIS
Keywords
Field
DocType
crisp data,fuzzy logic,fuzzy datalog program,flexible querying,data model,fuzzy interpretation,vague expression,computational model,fuzzy knowledge base,fuzzy similarity,fuzzy fixpoint operator,computer model,scoring rule,relation algebra,knowledge base,expressive power
Data mining,Neuro-fuzzy,Fuzzy classification,Defuzzification,Fuzzy set operations,Computer science,Fuzzy logic,Fuzzy mathematics,Artificial intelligence,Fuzzy number,Type-2 fuzzy sets and systems,Database
Conference
ISBN
Citations 
PageRank 
3-540-42555-1
10
0.99
References 
Authors
7
2
Name
Order
Citations
PageRank
Jaroslav Pokorný1760128.47
Peter Vojtás233633.41