An Open Source Framework for

Fuzzy Representation and

Querying in Databases

José Enrique Pons Frías

Olga Pons Capote

Ignacio Blanco Medina

Contents

Fuzzy databases Hibernate Framework Applications Conclusions and future work

Fuzzy Databases

Fuzzy Databases

Flexible querying select every people

which are in its thirties.

#ID Name Age Eye Color

Hair Color

1 Peter 24 Brown Blonde

2 Maria 34 Blue Blonde

3 John 52 Brown Brown

4 Sarah 29 Green Brown

Fuzzy Databases

Flexible querying select every people

which are in its thirties.

#ID Name Age Eye Color

Hair Color

1 Peter 24 Brown Blonde

2 Maria 34 Blue Blonde

3 John 52 Brown Brown

4 Sarah 29 Green Brown

Fuzzy Databases

Fuzzy Datatypes Fuzzy datatypes in an

ordered underlying domain.

#ID Name Age Eye Color

Hair Color

1 Peter Brown Blonde

2 Maria 'Young' Blue Blonde

3 John UNKNOWN

Brown Brown

4 Sarah 29 Green Brown

Fuzzy Databases

Fuzzy Datatypes Fuzzy data types in an

underlying non-ordered domain

#ID Name Age Eye Color

Hair Color

1 Peter 24 Brown Blonde

2 Maria 34 Blue Blonde

3 John 52 Brown Brown

4 Sarah 29 Green Brown

Fuzzy Databases

Fuzzy Datatypes Fuzzy data types in an

underlying non-ordered domain

#ID Name Age Eye Color

Hair Color

1 Peter 24 Brown Blonde

2 Maria 34 Blue Blonde

3 John 52 Brown Brown

4 Sarah 29 Green Brown

Brown Blue Green

Brown 1 0.1 0.1

Blue 1 0.6

Green 1

Fuzzy compatibility degrees:

Fuzzy Databases

Fuzzy operators: FEQ: Fuzzy Equals FGT: Fuzzy Greater than …

Necessity operators: NEQ: Necessity Equal...

FLEQ operator

Trapezoid poss. dist.

Hibernate Framework

Applications

Hibernate Framework Hibernate OR mapping. Querying in Hibernate. Fuzzy Data types in Hibernate Flexible querying in Hibernate Fuzzy temporal data types and operators.

Hibernate Framework

MySQL, Oracle, PosgreSQL, O2, HsqlDb, ...,

An Open Source Frameworkfor Object-relational mapping

Hibernate Framework Apps

www.facturae.es

PLAMSI

Mapache Server

Hibernate O-R-Mapping

Person{

Name

SurName

Age

Gender

…

Login

Password

}

==

=

=

=

=

Rs[0];Rs[1];

Rs[2];

Rs[3];

…

Rs[N-1];

Rs[N];

Without Hibernate, after a query, the resultset must be fitted field by field in the object

Hibernate O-R-Mapping

Person{

Name

SurName

Age

Gender

…

Login

Password

}

==

=

=

=

=

Rs[0];Rs[1];

Rs[2];

Rs[3];

…

Rs[N-1];

Rs[N];

Without Hibernate, after a query, the resulset must be fitted field by field in the object

Querying in Hibernate Framework

Query by criteria: A more complex selection method. Selects objects that fulfill a set of criteria.

Query by example: Selects objects similar to a given object.

HQL: Hibernate Query Language: An object oriented query language.

SQL: An SQL sentence.

createCriteria(Person.class).Add(Restrictions.eq(“login”, ”jpons”));

Person p;p.login = “jpons”;

“Select p from Person pWhere p.login = 'jpons'”;

“Select * from Person p where p.login = 'jpons'”;

Querying in Hibernate Framework

Query by criteria: A more complex selection method. Selects objects that fulfill a set of criteria.

Query by example: Selects objects similar to a given object.

HQL: Hibernate Query Language: An object oriented query language.

SQL: An SQL sentence.

createCriteria(Person.class).Add(Restrictions.eq(“login”, ”jpons”));

Person p;p.login = “jpons”;

“Select p from Person pWhere p.login = 'jpons'”;

“Select * from Person p where p.login = 'jpons'”;

Each query is translated into a SQL sentence

Query translationHQL sentence: “Select p from Personal where p.login like 'lmmn';

SQL sentence: “Select * from Personal as p where p.login like 'lmmn';

AST: Abstract Sintax Tree

Select

p from

Personal whereThrough the dialect

Fuzzy datatypes in Hibernate

Allows definition of new fuzzy domains:

Fuzzy Domains in underlying ordered domain.

Fuzzy Domains in underlying non-ordered domain.

Any relational database supported by Hibernate, allows fuzzy data types now !

Fuzzy datatypes in Hibernate

Fuzzy Datatypes Fuzzy datatypes in an

ordered underlying domain.

#ID Name Age Eye Color

Hair Color

1 Peter Brown Blonde

2 Maria 34 Blue Blonde

3 John 52 Brown Brown

4 Sarah 29 Green Brown

Fuzzy Databases in Hibernate

Fuzzy Datatypes Fuzzy data types in an

underlying non-ordered domain

#ID Name Age Eye Color

Hair Color

1 Peter 24 Brown Blonde

2 Maria 34 Blue Blonde

3 John 52 Brown Brown

4 Sarah 29 Green Brown

Brown Blue Green

Brown 1 0.1 0.1

Blue 1 0.6

Green 1

Fuzzy compatibility degrees:

Fuzzy querying in Hibernate

Two conditions met:

Declarative implementation of Fuzzy operators in SQL.

The AST is modified when a fuzzy operator is applied to a fuzzy type.

Declarative implementationCASE WHEN 1≤2 ∨1≥2 THEN 0

CASE WHEN 1=2 THEN 1

CASE WHEN 12∧12 THEN round 1−21−2

ELSE round 2−112

AST modification

p.age

FEQ

'young'

where

HQL: “Select p From Personal where p.age FEQ 'young';”

...

In the translation process from AST to SQL, the FEQ node is modified..

Select * From Personal as p where 1 < CASE WHEN (p.age.alfa<= beta2) OR (p.age.beta >=alfa2) THEN 0WHEN (p.age.alfa = alfa2) THEN 1WHEN (p.age.beta > beta2) AND (p.age.alfa < alfa2)

THEN round( (p.age.alfa – beta2) / (p.age.delta – delta2),2)ELSE round ( (alfa2 – p.age.beta) / (p.age.delta + delta2)”

Applications

Selection of target customers

#ID Name Surname Age Average Balance

1 Peter Parker 26 1500€

2 Ann Green 30 1100€

3 Laurie Doe 19 600€

Customers table

#ID Service Name

Target Age

1 Rechargeable credit card

'Young'

2 Low rate mortgage

'Middle-Age'

Table with services and fuzzy attribute 'target age'

Selection of target customers

Obtaining the most interesting customer for each service:

SELECT s,c FROM Customers c, Services s WHERE c.age FEQ s.targetAge

s.#ID s.Service Name

s.Target Age c.#ID c.Name ... Age Compatibility

1 Rechargeable credit card

'Young' 1 Peter ... 26 0.1

1 Rechargeable credit card

'Young' 3 Laurie ... 19 1

2 Low rate mortgage

'Middle-Age' 1 Peter ... 26 0.9

2 Low rate mortgage

'Middle-Age' 2 Ann ... 30 1

Conclusions

Fuzzy querying and fuzzy representation is now possible in almost any relational database supported by the framework.

Future work

Representation of fuzzy temporal information.

Extension of the model for bipolar queries.

New applications with fuzzy temporal and bipolar information.

Thank you

+ Info: Hibernate: www.hibernate.org

Email: jpons@decsai.ugr.es