On diverse answers issued from flexible queries

1998 ◽  
pp. 55-67
Author(s):  
Patrick Bosc
Keyword(s):  
Flexible Queries

scholarly journals The Burkholderia Genome Database: facilitating flexible queries and comparative analyses

2008 ◽  
Vol 24 (23) ◽  
pp. 2803-2804 ◽  
Author(s):  
G. L. Winsor ◽  
B. Khaira ◽  
T. Van Rossum ◽  
R. Lo ◽  
M. D. Whiteside ◽  
...  
Keyword(s):  
Genome Database ◽  
Comparative Analyses ◽  
Flexible Queries

PACS archive server database structure enabling flexible queries

2003 ◽  
Author(s):  
Sam Z. Shen ◽  
Martin J. Yaffe ◽  
Zhongming Chen ◽  
Gordon E. Mawdsley
Keyword(s):  
Database Structure ◽  
Flexible Queries

On the Versatility of Fuzzy Sets for Modeling Flexible Queries

2011 ◽  
pp. 143-166
Author(s):  
P Bosc ◽  
A Hadjali ◽  
O Pivert
Keyword(s):  
Fuzzy Sets ◽  
Point Of View ◽  
Flexible Queries ◽  
Boolean Queries ◽  
Natural Means ◽  
User Queries

The idea of extending the usual Boolean queries with preferences has become a hot topic in the database community. One of the advantages of this approach is to deliver discriminated answers rather than flat sets of elements. Fuzzy sets are a natural means to represent preferences, and many works have been undertaken to define queries where fuzzy predicates can be introduced inside user queries. The objective of this chapter is to illustrate the expressiveness of fuzzy sets with the division operator in the context of regular databases. Like other operators, the regular division is not flexible at all and small variations in the data may lead to totally different results. To counter this behavior, a variety of extended division operators founded on fuzzy sets are suggested. All of them obey a double requirement: to have a clear meaning from a user point of view and to deliver a resulting relation which is a quotient.

From User Requirements to Evaluation Strategies of Flexible Queries in Databases

2011 ◽  
pp. 115-142
Author(s):  
Noureddine Mouaddib ◽  
Guillaume Raschia ◽  
W. Amenel Voglozin ◽  
Laurent Ughetto
Keyword(s):  
User Requirements ◽  
Index Structures ◽  
Access Methods ◽  
Query Formulation ◽  
Whole Process ◽  
Evaluation Strategies ◽  
Flexible Queries ◽  
Fuzzy Labels

This chapter presents a discussion on fuzzy querying. It deals with the whole process of fuzzy querying, from the query formulation to its evaluation. Mainly, it advocates the use of index structures in the evaluation of fuzzy queries. First, various ways of introducing flexibility in querying processes are discussed, especially the most represented in the literature, which are based on rankings of the answers or which are using user-oriented fuzzy labels in the queries. Current methods for evaluating fuzzy queries are also reviewed. Then, properties of access methods are given in the context of fuzzy querying. Last, SaintEtiQ, the method developed in our team, is briefly presented.

Dynamic user profiles and flexible queries in office document retrieval systems

1989 ◽  
Vol 5 (1) ◽  
pp. 13-28 ◽  
Author(s):  
F.A. Schreiber ◽  
F. Barbic ◽  
S. Madeddu
Keyword(s):  
Document Retrieval ◽  
User Profiles ◽  
Retrieval Systems ◽  
Flexible Queries ◽  
Office Document

Flexible queries in 3D searching. 2. Techniques in 3D query formulation

1990 ◽  
Vol 3 (6) ◽  
pp. 557-563 ◽  
Author(s):  
Osman F. Güner ◽  
Douglas R. Henry ◽  
Thomas E. Moock ◽  
Robert S. Pearlman
Keyword(s):  
Query Formulation ◽  
Flexible Queries

A Fuzzy Ontology-Based Platform for Flexible Querying

2015 ◽  
Vol 6 (3) ◽  
pp. 12-26 ◽  
Author(s):  
Amira Aloui ◽  
Amel Grissa Touzi
Keyword(s):  
Fuzzy Logic ◽  
Initial Data ◽  
Data Retrieval ◽  
Conceptual Clustering ◽  
Large Databases ◽  
Flexible Queries ◽  
Definition Of ◽  
Preliminary Classification ◽  
Flexible Querying

Flexible queries have recently received increasing attention to better characterize the data retrieval. In this paper, a new flexible querying approach using ontological knowledge is proposed. This approach presents an FCA based methodology for building ontologies from scratch then interrogating them intelligently through the fusion of conceptual clustering, fuzzy logic, and FCA. The main contribution is the definition of the ontology rom classes resulting from a preliminary classification of the data and not the initial data. The data cleansing provides a simple ontology and an optimal research of relevant data taking into account the preferences cited by the user in his initial interrogation. To realize this approach, a new platform called “FO-FQ Tab plug-in” is implemented. This plug-in is integrated within the ontology editor Protégé to allow building fuzzy ontologies from large databases and querying them intelligently

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