Fuzzy preference queries to relational databases /:
The manipulation of databases is an integral part of a world which is becoming increasingly and pervasively information-focused. This book puts forward a suggestion to advocate preference queries and fuzzy sets as a central concern in database queries and offers an important contribution to the desi...
Gespeichert in:
| 1. Verfasser: | |
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| Weitere Verfasser: | |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London :
Imperial College Press,
2012.
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| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | The manipulation of databases is an integral part of a world which is becoming increasingly and pervasively information-focused. This book puts forward a suggestion to advocate preference queries and fuzzy sets as a central concern in database queries and offers an important contribution to the design of intelligent information systems. It provides a comprehensive study on fuzzy preference queries in the context of relational databases. Preference queries, a recent hot topic in database research, provide a basis for rank-ordering the items retrieved, which is especially valuable for large sets of answers. This book aims to show that fuzzy set theory constitutes a highly expressive framework for modeling preference queries. It presents a study of the algorithmic aspects related to the evaluation of such queries in order to demonstrate that this framework offers a good trade-off between expressivity and efficiency. Numerous examples and proofs are liberally and lucidly demonstrated throughout and greatly enhance the detailed theoretical aspects explored in the book. Researchers working in databases will greatly benefit from this comprehensive and up-to-date study of fuzzy preference queries and it will also become an invaluable reference point for postgraduate students interested in advanced database techniques. |
| Beschreibung: | 1 online resource : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781848168701 1848168705 |
Internformat
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| 505 | 0 | |a 1. Introduction. 1.1. Databases and their evolution. 1.2. Preferences and fuzzy sets. 1.3. Overview of the book -- 2. Reminders on relational databases. 2.1. Basic notions and vocabulary. 2.2. Algebraic operations. 2.3. An overview of SQL -- 3. Basic notions on fuzzy sets. 3.1. Introduction. 3.2. Definitions and notations. 3.3. Composition of fuzzy sets. 3.4. Inclusions and implications. 3.5. Fuzzy measures and integrals. 3.6. The extension principle. 3.7. Fuzzy quantified propositions -- 4. Non-fuzzy approaches to preference queries: a brief overview. 4.1. Introduction. 4.2. Quantitative approaches. 4.3. Qualitative approaches. 4.4. Conclusion -- 5. Simple fuzzy queries. 5.1. Introduction. 5.2. An extended relational algebra. 5.3. An overview of a basic version of SQLf. 5.4. Interface for user-defined terms and operators. 5.5. Contextual queries. 5.6. Evaluation of simple fuzzy queries. 5.7. Conclusion -- 6. Fuzzy queries involving quantified statements or aggregates. 6.1. Introduction. 6.2. Quantified statements. 6.3. Aggregates. 6.4. Conclusion -- 7. Division and antidivision of fuzzy relations. 7.1. Introduction. 7.2. Division of fuzzy relations. 7.3. Tolerant division. 7.4. Stratified division. 7.5. Queries mixing division and antidivision. 7.6. Evaluation of division queries. 7.7. Conclusion -- 8. Bipolar fuzzy queries. 8.1. Introduction. 8.2. Preliminaries. 8.3. Extended algebraic operators. 8.4. Implementation aspects. 8.5. Conclusion -- 9. Fuzzy group by. 9.1. Introduction. 9.2. An extended group by clause. 9.3. Having clause. 9.4. Application to association rule mining. 9.5. Evaluation of a fuzzy group by. 9.6. Related work. 9.7. Conclusion -- 10. Empty and plethoric answers. 10.1. Introduction. 10.2. Empty answer problem. 10.3. Plethoric answer problem. 10.4. Conclusion -- 11. Conclusion. | |
| 520 | |a The manipulation of databases is an integral part of a world which is becoming increasingly and pervasively information-focused. This book puts forward a suggestion to advocate preference queries and fuzzy sets as a central concern in database queries and offers an important contribution to the design of intelligent information systems. It provides a comprehensive study on fuzzy preference queries in the context of relational databases. Preference queries, a recent hot topic in database research, provide a basis for rank-ordering the items retrieved, which is especially valuable for large sets of answers. This book aims to show that fuzzy set theory constitutes a highly expressive framework for modeling preference queries. It presents a study of the algorithmic aspects related to the evaluation of such queries in order to demonstrate that this framework offers a good trade-off between expressivity and efficiency. Numerous examples and proofs are liberally and lucidly demonstrated throughout and greatly enhance the detailed theoretical aspects explored in the book. Researchers working in databases will greatly benefit from this comprehensive and up-to-date study of fuzzy preference queries and it will also become an invaluable reference point for postgraduate students interested in advanced database techniques. | ||
| 504 | |a Includes bibliographical references and index. | ||
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| contents | 1. Introduction. 1.1. Databases and their evolution. 1.2. Preferences and fuzzy sets. 1.3. Overview of the book -- 2. Reminders on relational databases. 2.1. Basic notions and vocabulary. 2.2. Algebraic operations. 2.3. An overview of SQL -- 3. Basic notions on fuzzy sets. 3.1. Introduction. 3.2. Definitions and notations. 3.3. Composition of fuzzy sets. 3.4. Inclusions and implications. 3.5. Fuzzy measures and integrals. 3.6. The extension principle. 3.7. Fuzzy quantified propositions -- 4. Non-fuzzy approaches to preference queries: a brief overview. 4.1. Introduction. 4.2. Quantitative approaches. 4.3. Qualitative approaches. 4.4. Conclusion -- 5. Simple fuzzy queries. 5.1. Introduction. 5.2. An extended relational algebra. 5.3. An overview of a basic version of SQLf. 5.4. Interface for user-defined terms and operators. 5.5. Contextual queries. 5.6. Evaluation of simple fuzzy queries. 5.7. Conclusion -- 6. Fuzzy queries involving quantified statements or aggregates. 6.1. Introduction. 6.2. Quantified statements. 6.3. Aggregates. 6.4. Conclusion -- 7. Division and antidivision of fuzzy relations. 7.1. Introduction. 7.2. Division of fuzzy relations. 7.3. Tolerant division. 7.4. Stratified division. 7.5. Queries mixing division and antidivision. 7.6. Evaluation of division queries. 7.7. Conclusion -- 8. Bipolar fuzzy queries. 8.1. Introduction. 8.2. Preliminaries. 8.3. Extended algebraic operators. 8.4. Implementation aspects. 8.5. Conclusion -- 9. Fuzzy group by. 9.1. Introduction. 9.2. An extended group by clause. 9.3. Having clause. 9.4. Application to association rule mining. 9.5. Evaluation of a fuzzy group by. 9.6. Related work. 9.7. Conclusion -- 10. Empty and plethoric answers. 10.1. Introduction. 10.2. Empty answer problem. 10.3. Plethoric answer problem. 10.4. Conclusion -- 11. Conclusion. |
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| dewey-search | 006.3/3 |
| dewey-sort | 16.3 13 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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Introduction. 1.1. Databases and their evolution. 1.2. Preferences and fuzzy sets. 1.3. Overview of the book -- 2. Reminders on relational databases. 2.1. Basic notions and vocabulary. 2.2. Algebraic operations. 2.3. An overview of SQL -- 3. Basic notions on fuzzy sets. 3.1. Introduction. 3.2. Definitions and notations. 3.3. Composition of fuzzy sets. 3.4. Inclusions and implications. 3.5. Fuzzy measures and integrals. 3.6. The extension principle. 3.7. Fuzzy quantified propositions -- 4. Non-fuzzy approaches to preference queries: a brief overview. 4.1. Introduction. 4.2. Quantitative approaches. 4.3. Qualitative approaches. 4.4. Conclusion -- 5. Simple fuzzy queries. 5.1. Introduction. 5.2. An extended relational algebra. 5.3. An overview of a basic version of SQLf. 5.4. Interface for user-defined terms and operators. 5.5. Contextual queries. 5.6. Evaluation of simple fuzzy queries. 5.7. Conclusion -- 6. Fuzzy queries involving quantified statements or aggregates. 6.1. Introduction. 6.2. Quantified statements. 6.3. Aggregates. 6.4. Conclusion -- 7. Division and antidivision of fuzzy relations. 7.1. Introduction. 7.2. Division of fuzzy relations. 7.3. Tolerant division. 7.4. Stratified division. 7.5. Queries mixing division and antidivision. 7.6. Evaluation of division queries. 7.7. Conclusion -- 8. Bipolar fuzzy queries. 8.1. Introduction. 8.2. Preliminaries. 8.3. Extended algebraic operators. 8.4. Implementation aspects. 8.5. Conclusion -- 9. Fuzzy group by. 9.1. Introduction. 9.2. An extended group by clause. 9.3. Having clause. 9.4. Application to association rule mining. 9.5. Evaluation of a fuzzy group by. 9.6. Related work. 9.7. Conclusion -- 10. Empty and plethoric answers. 10.1. Introduction. 10.2. Empty answer problem. 10.3. Plethoric answer problem. 10.4. Conclusion -- 11. 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| publisher | Imperial College Press, |
| record_format | marc |
| spelling | Pivert, Olivier. http://id.loc.gov/authorities/names/no2012099623 Fuzzy preference queries to relational databases / Olivier Pivert & Patrick Bosc. London : Imperial College Press, 2012. 1 online resource : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Print version record. 1. Introduction. 1.1. Databases and their evolution. 1.2. Preferences and fuzzy sets. 1.3. Overview of the book -- 2. Reminders on relational databases. 2.1. Basic notions and vocabulary. 2.2. Algebraic operations. 2.3. An overview of SQL -- 3. Basic notions on fuzzy sets. 3.1. Introduction. 3.2. Definitions and notations. 3.3. Composition of fuzzy sets. 3.4. Inclusions and implications. 3.5. Fuzzy measures and integrals. 3.6. The extension principle. 3.7. Fuzzy quantified propositions -- 4. Non-fuzzy approaches to preference queries: a brief overview. 4.1. Introduction. 4.2. Quantitative approaches. 4.3. Qualitative approaches. 4.4. Conclusion -- 5. Simple fuzzy queries. 5.1. Introduction. 5.2. An extended relational algebra. 5.3. An overview of a basic version of SQLf. 5.4. Interface for user-defined terms and operators. 5.5. Contextual queries. 5.6. Evaluation of simple fuzzy queries. 5.7. Conclusion -- 6. Fuzzy queries involving quantified statements or aggregates. 6.1. Introduction. 6.2. Quantified statements. 6.3. Aggregates. 6.4. Conclusion -- 7. Division and antidivision of fuzzy relations. 7.1. Introduction. 7.2. Division of fuzzy relations. 7.3. Tolerant division. 7.4. Stratified division. 7.5. Queries mixing division and antidivision. 7.6. Evaluation of division queries. 7.7. Conclusion -- 8. Bipolar fuzzy queries. 8.1. Introduction. 8.2. Preliminaries. 8.3. Extended algebraic operators. 8.4. Implementation aspects. 8.5. Conclusion -- 9. Fuzzy group by. 9.1. Introduction. 9.2. An extended group by clause. 9.3. Having clause. 9.4. Application to association rule mining. 9.5. Evaluation of a fuzzy group by. 9.6. Related work. 9.7. Conclusion -- 10. Empty and plethoric answers. 10.1. Introduction. 10.2. Empty answer problem. 10.3. Plethoric answer problem. 10.4. Conclusion -- 11. Conclusion. The manipulation of databases is an integral part of a world which is becoming increasingly and pervasively information-focused. This book puts forward a suggestion to advocate preference queries and fuzzy sets as a central concern in database queries and offers an important contribution to the design of intelligent information systems. It provides a comprehensive study on fuzzy preference queries in the context of relational databases. Preference queries, a recent hot topic in database research, provide a basis for rank-ordering the items retrieved, which is especially valuable for large sets of answers. This book aims to show that fuzzy set theory constitutes a highly expressive framework for modeling preference queries. It presents a study of the algorithmic aspects related to the evaluation of such queries in order to demonstrate that this framework offers a good trade-off between expressivity and efficiency. Numerous examples and proofs are liberally and lucidly demonstrated throughout and greatly enhance the detailed theoretical aspects explored in the book. Researchers working in databases will greatly benefit from this comprehensive and up-to-date study of fuzzy preference queries and it will also become an invaluable reference point for postgraduate students interested in advanced database techniques. Includes bibliographical references and index. Expert systems (Computer science) http://id.loc.gov/authorities/subjects/sh85046450 Uncertainty (Information theory) http://id.loc.gov/authorities/subjects/sh85139564 Systèmes experts (Informatique) Incertitude (Théorie de l'information) COMPUTERS Expert Systems. bisacsh Expert systems (Computer science) fast Uncertainty (Information theory) fast databases. aat Databases fast Databases. lcgft http://id.loc.gov/authorities/genreForms/gf2014026081 Bases de données. rvmgf Bosc, Patrick. http://id.loc.gov/authorities/names/n95101243 has work: Fuzzy preference queries to relational databases (Text) https://id.oclc.org/worldcat/entity/E39PCG6g74PvP6XG69KjTqgtKd https://id.oclc.org/worldcat/ontology/hasWork Print version: Pivert, Olivier. Fuzzy preference queries to relational databases. London : Imperial College Press, 2012 9781848168695 (OCoLC)756598002 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=457190 Volltext |
| spellingShingle | Pivert, Olivier Fuzzy preference queries to relational databases / 1. Introduction. 1.1. Databases and their evolution. 1.2. Preferences and fuzzy sets. 1.3. Overview of the book -- 2. Reminders on relational databases. 2.1. Basic notions and vocabulary. 2.2. Algebraic operations. 2.3. An overview of SQL -- 3. Basic notions on fuzzy sets. 3.1. Introduction. 3.2. Definitions and notations. 3.3. Composition of fuzzy sets. 3.4. Inclusions and implications. 3.5. Fuzzy measures and integrals. 3.6. The extension principle. 3.7. Fuzzy quantified propositions -- 4. Non-fuzzy approaches to preference queries: a brief overview. 4.1. Introduction. 4.2. Quantitative approaches. 4.3. Qualitative approaches. 4.4. Conclusion -- 5. Simple fuzzy queries. 5.1. Introduction. 5.2. An extended relational algebra. 5.3. An overview of a basic version of SQLf. 5.4. Interface for user-defined terms and operators. 5.5. Contextual queries. 5.6. Evaluation of simple fuzzy queries. 5.7. Conclusion -- 6. Fuzzy queries involving quantified statements or aggregates. 6.1. Introduction. 6.2. Quantified statements. 6.3. Aggregates. 6.4. Conclusion -- 7. Division and antidivision of fuzzy relations. 7.1. Introduction. 7.2. Division of fuzzy relations. 7.3. Tolerant division. 7.4. Stratified division. 7.5. Queries mixing division and antidivision. 7.6. Evaluation of division queries. 7.7. Conclusion -- 8. Bipolar fuzzy queries. 8.1. Introduction. 8.2. Preliminaries. 8.3. Extended algebraic operators. 8.4. Implementation aspects. 8.5. Conclusion -- 9. Fuzzy group by. 9.1. Introduction. 9.2. An extended group by clause. 9.3. Having clause. 9.4. Application to association rule mining. 9.5. Evaluation of a fuzzy group by. 9.6. Related work. 9.7. Conclusion -- 10. Empty and plethoric answers. 10.1. Introduction. 10.2. Empty answer problem. 10.3. Plethoric answer problem. 10.4. Conclusion -- 11. Conclusion. Expert systems (Computer science) http://id.loc.gov/authorities/subjects/sh85046450 Uncertainty (Information theory) http://id.loc.gov/authorities/subjects/sh85139564 Systèmes experts (Informatique) Incertitude (Théorie de l'information) COMPUTERS Expert Systems. bisacsh Expert systems (Computer science) fast Uncertainty (Information theory) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85046450 http://id.loc.gov/authorities/subjects/sh85139564 http://id.loc.gov/authorities/genreForms/gf2014026081 |
| title | Fuzzy preference queries to relational databases / |
| title_auth | Fuzzy preference queries to relational databases / |
| title_exact_search | Fuzzy preference queries to relational databases / |
| title_full | Fuzzy preference queries to relational databases / Olivier Pivert & Patrick Bosc. |
| title_fullStr | Fuzzy preference queries to relational databases / Olivier Pivert & Patrick Bosc. |
| title_full_unstemmed | Fuzzy preference queries to relational databases / Olivier Pivert & Patrick Bosc. |
| title_short | Fuzzy preference queries to relational databases / |
| title_sort | fuzzy preference queries to relational databases |
| topic | Expert systems (Computer science) http://id.loc.gov/authorities/subjects/sh85046450 Uncertainty (Information theory) http://id.loc.gov/authorities/subjects/sh85139564 Systèmes experts (Informatique) Incertitude (Théorie de l'information) COMPUTERS Expert Systems. bisacsh Expert systems (Computer science) fast Uncertainty (Information theory) fast |
| topic_facet | Expert systems (Computer science) Uncertainty (Information theory) Systèmes experts (Informatique) Incertitude (Théorie de l'information) COMPUTERS Expert Systems. databases. Databases Databases. Bases de données. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=457190 |
| work_keys_str_mv | AT pivertolivier fuzzypreferencequeriestorelationaldatabases AT boscpatrick fuzzypreferencequeriestorelationaldatabases |