Flexible queries on relational databases using fuzzy logic and ontologies

Combines fuzzy logic and semantic techniques to perform flexible queries in a relational database.Alternative method to fuzzy logic, to execute flexible queries on non-scalar attributes.Answers are ordered according with the accomplishment degree to the query.Ontologies are used as an attribute domain frame to return semantically similar information to the query.Fuzzy logic are used on scalar attributes. Nowadays there are many proposals that allow users to perform fuzzy queries on relational databases. Regardless of these proposals, fuzzy queries are really useful on scalar values where fuzzy sets can be adjusted to the user needs and domains, but non-scalar values are a more complex task. Here, we extend non-scalar attribute management in fuzzy queries with the use of ontologies. Thus, we allow to compute this kind of queries not only with the similarity relationships defined explicitly on a fuzzy set but with semantically interrelated terms modeled as a domain ontology as well. Moreover, we present the architecture of a novel system that combines both techniques to return an answer as much complete as possible and ordered by a degree of accomplishment. Finally, a qualitative and quantitative study about the use of flexible queries on relational databases is included in this work, as well.

[1]  Elke A. Rundensteiner,et al.  On nearness measures in fuzzy relational data models , 1989, Int. J. Approx. Reason..

[2]  Johann-Christoph Freytag,et al.  Ontology Based Query Processing in Database Management Systems , 2003, OTM.

[3]  David W. Embley,et al.  Towards Ontology Generation from Tables , 2005, World Wide Web.

[4]  Asunción Gómez-Pérez,et al.  Fund Finder: A case study of database-to-ontology mapping , 2003 .

[5]  Zongmin Ma,et al.  Fuzzy Database Modeling of Imprecise and Uncertain Engineering Information , 2006 .

[6]  L. Stein,et al.  OWL Web Ontology Language - Reference , 2004 .

[7]  Ollivier Haemmerlé,et al.  Fuzzy querying of incomplete, imprecise, and heterogeneously structured data in the relational model using ontologies and rules , 2005, IEEE Transactions on Fuzzy Systems.

[8]  Mario Piattini,et al.  Handbook of Research on Web Information Systems Quality , 2008 .

[9]  J. Kacprzyk,et al.  SQLf and FQUERY for Access , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[10]  Douglas B. Lenat,et al.  CYC: a large-scale investment in knowledge infrastructure , 1995, CACM.

[11]  Graeme Hirst,et al.  Lexical chains as representations of context for the detection and correction of malapropisms , 1995 .

[12]  Juan Manuel Serrano,et al.  Using fuzzy relational databases to represent agricultural and environmental information. An example within the scope of olive cultivation in Granada. , 2001 .

[13]  M. Amparo Vila,et al.  An Ontology as a Tool for Representing Fuzzy Data in Relational Databases , 2012, Int. J. Comput. Intell. Syst..

[14]  Olga Pons,et al.  GEFRED: A Generalized Model of Fuzzy Relational Databases , 1994, Inf. Sci..

[15]  David Sánchez,et al.  Ontology-based semantic similarity: A new feature-based approach , 2012, Expert Syst. Appl..

[16]  Frank van Harmelen,et al.  Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema , 2002, SEMWEB.

[17]  Yamine Aït Ameur,et al.  Domain Ontologies: A Database-Oriented Analysis , 2006, WEBIST.

[18]  M. Umano,et al.  Fuzzy database systems , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[19]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[20]  Enrico Motta,et al.  Watson, more than a Semantic Web search engine , 2011, Semantic Web.

[21]  J. van Leeuwen,et al.  Advanced Information Systems Engineering , 1999, Lecture Notes in Computer Science.

[22]  Mario Piattini,et al.  An ontological approach to describe the SQL: 2003 object-relational features , 2006, Comput. Stand. Interfaces.

[23]  Eduard Constantin Dragut,et al.  Composing Mappings Between Schemas Using a Reference Ontology , 2004, CoopIS/DOA/ODBASE.

[24]  Ladjel Bellatreche,et al.  OntoDB: It Is Time to Embed Your Domain Ontology in Your Database , 2007, DASFAA.

[25]  Irina Astrova,et al.  Reverse Engineering of Relational Databases to Ontologies , 2004, ESWS.

[26]  Jun Zhang,et al.  Si-SEEKER: Ontology-Based Semantic Search over Databases , 2006, KSEM.

[27]  Henri Prade,et al.  Generalizing Database Relational Algebra for the Treatment of Incomplete/Uncertain Information and Vague Queries , 1984, Inf. Sci..

[28]  F. E. A Relational Model of Data Large Shared Data Banks , 2000 .

[29]  M. Amparo Vila,et al.  Ontologies versus relational databases: are they so different? A comparison , 2012, Artificial Intelligence Review.

[30]  Irina Astrova Extracting Ontologies from Relational Databases , 2004, Databases and Applications.

[31]  Sean Bechhofer,et al.  The OWL API: A Java API for OWL ontologies , 2011, Semantic Web.

[32]  Nikolas Mitrou,et al.  VisAVis: An Approach to an Intermediate Layer between Ontologies and Relational Database Contents , 2006, WISM.

[33]  Jing Liu,et al.  Robust Structured Subspace Learning for Data Representation , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[34]  Jing Liu,et al.  Clustering-Guided Sparse Structural Learning for Unsupervised Feature Selection , 2014, IEEE Transactions on Knowledge and Data Engineering.

[35]  B. Buckles,et al.  A fuzzy representation of data for relational databases , 1982 .

[36]  Nikolas Mitrou,et al.  Ontology and Database Mapping: A Survey of Current Implementations and Future Directions , 2008, J. Web Eng..

[37]  Abraham Kandel,et al.  Implementing Imprecision in Information Systems , 1985, Inf. Sci..

[38]  Johann-Christoph Freytag,et al.  Query Processing Using Ontologies , 2005, CAiSE.

[39]  Patrick Bosc,et al.  SQLf: a relational database language for fuzzy querying , 1995, IEEE Trans. Fuzzy Syst..

[40]  E. F. CODD,et al.  A relational model of data for large shared data banks , 1970, CACM.

[41]  Stefan Conrad,et al.  Relational.OWL - A Data and Schema Representation Format Based on OWL , 2005, APCCM.

[42]  Meng Wang,et al.  Neighborhood Discriminant Hashing for Large-Scale Image Retrieval , 2015, IEEE Transactions on Image Processing.

[43]  Vipul Kashyap,et al.  Design and Creation of Ontologies for Environmental Information Retrieval1 , 1999 .