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Recent issues on fuzzy databases
Fuzzy Sets and Systems 140 (2003) 229 – 230
www.elsevier.com/locate/fss
Book review Recent issues on fuzzy databases G. Bordogna, and G. Pasi (Eds.); Physica Verlag, Wurzburg, 2000, 236pp., ISBN: 3-7908-1319-2 Introduction Fuzzy database systems have been an active research 4eld for more than 20 years. In spite of many achievements in recent times, relatively few books on this subject exist. This publication tries to narrow the gap by presenting a collection of scienti4c papers dealing with current research topics on fuzzy databases. A walk through the contents The book is divided into four major parts, each containing 2–3 papers written by di8erent authors. They deal with: the semantics of querying, data mining, geographic information systems (GIS), and data models, each in the context of fuzzy information. Let us have a closer look at the four parts: Part I: fuzzy querying of databases The 4rst paper of this part introduces a novel query framework in which the query conditions are regarded as constraints on the data representation. The second paper extends the relational division operator to fuzzy relational databases.
Part II: data mining based on fuzzy sets This part opens with a paper proposing a fuzzy extension to mining generalized association rules in the presence of fuzzy taxonomies. The second paper is about transforming data mining results into answers that are easier to grasp by users via fuzzy linguistic terms. Part III: geographic information systems dealing with uncertainty The 4rst paper covers data integration from different (GIS) data sources based on fuzzy sets. Issues of representing and managing uncertainty in the framework of the KBLIMS system is addressed in the second paper. The last paper of this part deals with modeling uncertainty in geographic applications on a conceptual level and mapping this model to a logical model (in this case FOOD). Part IV: fuzzy database models: de nition and implementation One paper of this part is about enhancing the ODMG object-orientated data model with representations of fuzzy and uncertain information. The remaining two papers cover implementation aspects of fuzzy database systems. One is about the implementation of deductive relational database systems that can handle fuzzy information, the other presents a prototype implementation for the FOOD data model.
c 2003 Elsevier B.V. All rights reserved. 0165-0114/03/$ - see front matter doi:10.1016/S0165-0114(03)00036-8
230
Book review / Fuzzy Sets and Systems 140 (2003) 229 – 230
Target audience The main audience of this book is researchers who want to gain an overview of current research topics in the 4eld of fuzzy databases. It may also be interesting to practitioners confronted with fuzzy information in their 4eld (e.g. geography) or engineers/computer scientists developing and implementing fuzzy database systems. However, some prior knowledge of fuzzy theory and databases is a prerequisite to reading this book, as it does not contain introductory material. Due to the diversity of the included papers probably not everything is of the same interest to every reader. Reviewer’s appreciation The main point of criticism is the lack of connections between the sections and papers. This can be explained by the diversity of topics and
the total number of authors. The only “glue” that keeps everything together is the general subject of fuzzy databases, so this book should be seen as a collection of papers on fuzzy databases. In a few places (e.g. in the paper on the fuzzy relational division operator) the motivations for the particular work could have been Eeshed out a little bit more. Overall, the book is a representative cross section of the current research issues in the area of fuzzy databases. The editors and authors are distinguished researchers in this 4eld with numerous publications to prove it. Sven Helmer Lehrstuhl f"ur Praktische Informatik III Universitu"at Mannheim Seminargebaude A5; C211 Mannheim 68131; Germany E-mail address: [email protected]
www.elsevier.com/locate/fss
Book review Recent issues on fuzzy databases G. Bordogna, and G. Pasi (Eds.); Physica Verlag, Wurzburg, 2000, 236pp., ISBN: 3-7908-1319-2 Introduction Fuzzy database systems have been an active research 4eld for more than 20 years. In spite of many achievements in recent times, relatively few books on this subject exist. This publication tries to narrow the gap by presenting a collection of scienti4c papers dealing with current research topics on fuzzy databases. A walk through the contents The book is divided into four major parts, each containing 2–3 papers written by di8erent authors. They deal with: the semantics of querying, data mining, geographic information systems (GIS), and data models, each in the context of fuzzy information. Let us have a closer look at the four parts: Part I: fuzzy querying of databases The 4rst paper of this part introduces a novel query framework in which the query conditions are regarded as constraints on the data representation. The second paper extends the relational division operator to fuzzy relational databases.
Part II: data mining based on fuzzy sets This part opens with a paper proposing a fuzzy extension to mining generalized association rules in the presence of fuzzy taxonomies. The second paper is about transforming data mining results into answers that are easier to grasp by users via fuzzy linguistic terms. Part III: geographic information systems dealing with uncertainty The 4rst paper covers data integration from different (GIS) data sources based on fuzzy sets. Issues of representing and managing uncertainty in the framework of the KBLIMS system is addressed in the second paper. The last paper of this part deals with modeling uncertainty in geographic applications on a conceptual level and mapping this model to a logical model (in this case FOOD). Part IV: fuzzy database models: de nition and implementation One paper of this part is about enhancing the ODMG object-orientated data model with representations of fuzzy and uncertain information. The remaining two papers cover implementation aspects of fuzzy database systems. One is about the implementation of deductive relational database systems that can handle fuzzy information, the other presents a prototype implementation for the FOOD data model.
c 2003 Elsevier B.V. All rights reserved. 0165-0114/03/$ - see front matter doi:10.1016/S0165-0114(03)00036-8
230
Book review / Fuzzy Sets and Systems 140 (2003) 229 – 230
Target audience The main audience of this book is researchers who want to gain an overview of current research topics in the 4eld of fuzzy databases. It may also be interesting to practitioners confronted with fuzzy information in their 4eld (e.g. geography) or engineers/computer scientists developing and implementing fuzzy database systems. However, some prior knowledge of fuzzy theory and databases is a prerequisite to reading this book, as it does not contain introductory material. Due to the diversity of the included papers probably not everything is of the same interest to every reader. Reviewer’s appreciation The main point of criticism is the lack of connections between the sections and papers. This can be explained by the diversity of topics and
the total number of authors. The only “glue” that keeps everything together is the general subject of fuzzy databases, so this book should be seen as a collection of papers on fuzzy databases. In a few places (e.g. in the paper on the fuzzy relational division operator) the motivations for the particular work could have been Eeshed out a little bit more. Overall, the book is a representative cross section of the current research issues in the area of fuzzy databases. The editors and authors are distinguished researchers in this 4eld with numerous publications to prove it. Sven Helmer Lehrstuhl f"ur Praktische Informatik III Universitu"at Mannheim Seminargebaude A5; C211 Mannheim 68131; Germany E-mail address: [email protected]