SQLf vs. Skyline - Expressivity and Performance

Gonçalves, Marlene; Tineo, Leonid

doi:10.1109/fuzzy.2006.1681986

Cited by 8 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Namely, there is no distinction between tuples that are dominated by fare and those that are near to dominant tuples. To solve this problem, recently a Fuzzy Dominance Skyline (FDS) has been proposed in [28,29]. It allows us to relax Skyline ordering by means of fuzzy dominance comparisons among tuples.…”

Section: Databases Approaches To Preference Handling In Queryingmentioning

confidence: 99%

Database preference queries—a possibilistic logic approach with symbolic priorities

Hadjali

Kaci

Prade

2011

Ann Math Artif Intell

View full text Add to dashboard Cite

The paper presents a new approach to database preference queries, where preferences are represented in a possibilistic logic manner, using symbolic weights. The symbolic weights may be processed without assessing their precise value, which leaves the freedom for the user to not specify any priority among the preferences. The user may also enforce a (partial) ordering between them, if necessary. The approach can be related to the processing of fuzzy queries whose components are conditionally weighted in terms of importance. In this paper, importance levels are symbolically processed, and refinements of both Pareto ordering and minimum ordering are used. The representational power of the proposed setting is stressed, while the approach is compared with database Best operator-like methods and with the CP-net approach developed in artificial intelligence. The paper also provides a structured and rather broad overview of the different lines of research in the literature dealing with the handling of preferences in database queries.

show abstract

Section: Databases Approaches To Preference Handling In Queryingmentioning

confidence: 99%

Database preference queries—a possibilistic logic approach with symbolic priorities

Hadjali

Kaci

Prade

2011

Ann Math Artif Intell

View full text Add to dashboard Cite

show abstract

“…Of course, fuzzy databases should allow fuzzy queries using fuzzy or nonfuzzy data, and there are some languages based on SQL (ANSI, 1992;Date & Darwen, 1997) that allow these kind of queries like FSQL (Galindo, 2007;Galindo et al, 2006) or SQLf (Bosc & Pivert, 1995;Goncalves & Tineo, 2006). The research on fuzzy databases has been developed for about 20 years and concentrated mainly on the following areas:…”

Section: Fuzzy Databasesmentioning

confidence: 99%

Introduction and Trends to Fuzzy Logic and Fuzzy Databases

Galindo

2008

Handbook of Research on Fuzzy Information Processing in Databases

View full text Add to dashboard Cite

This chapter presents an introduction to fuzzy logic and to fuzzy databases. With regard to the first topic, we have introduced the main concepts in this field to facilitate the understanding of the rest of the chapters to novel readers in fuzzy subjects. With respect to the fuzzy databases, this chapter gives a list of six research topics in this fuzzy area. All these topics are briefly commented on, and we include references to books, papers, and even to other chapters of this handbook, where we can find some interesting reviews about different subjects and new approaches with different goals. Finally, we give a historic summary of some fuzzy models, and we conclude with some future trends in this scientific area.

show abstract

“…We are interested in querying medical information, in particular for orthopedics, employing SQLf, a fuzzy querying language (Goncalves & Tineo, 2006), (Bosc & Pivert, 1995). It obeys to the fact that fuzzy sets are powerful manners to represent user preferences, imperfect data and weak relationships.…”

Section: Introductionmentioning

confidence: 99%

An Ontology in Orthopedic Medical Field

Vasquez¹,

Aguilera²,

Tineo³

2008

Proceedings of the Third International Conference on Software and Data Technologies Special Session on Applications in Banking

View full text Add to dashboard Cite

At present time, Ontology is a powerful Knowledge Representation tool for Web Information Retrieval and Mining. In particular, lots of medical applications in the field of diagnosis and tele-health would take advantage of information sharing and publication on the Web with the use of Ontology. We are especially interested in the field of orthopedic pathologies of human march. There are several laboratories in the world working in this topic but they are not exploiting potential of the Web in theirs works, they are almost isolate in information management. We have already carried out mining in database from the Venezuelan Hospital Ortopédico Infantil, nevertheless, it is necessary to build an ontology in order to query and mine information from different laboratories in the world. We would like in the near future to apply fuzzy logic techniques and fuzzy querying over such information. In this paper, we present the building of an orthopedic medical ontology, to the best of our knowledge, has not been reported other in this specific field that we are interested on.

show abstract

SQLf vs. Skyline - Expressivity and Performance

Cited by 8 publications

References 14 publications

Database preference queries—a possibilistic logic approach with symbolic priorities

Database preference queries—a possibilistic logic approach with symbolic priorities

Introduction and Trends to Fuzzy Logic and Fuzzy Databases

An Ontology in Orthopedic Medical Field

Contact Info

Product

Resources

About