Flexible Approaches in Data, Information and Knowledge Management

This volume showcases contributions from internationally-known researchers in the field of information management. Most of the approaches presented here make use of fuzzy logic, introduced by L.A. Zadeh almost 50 years ago, which constitute a powerful tool to model and handle gradual concepts. What all of these contributions have in common is placing the user at the center of the information system, be it for helping him/her to query a data set, to handle imperfect information, or to discover useful knowledge from a massive collection of data.

Researchers working in data and knowledge management will greatly benefit from this collection of up-to-date studies. This may be also an invaluable source of information for  postgraduate students interested in advanced information management techniques.

Table of Contents

Part I Bipolar Preference Queries
Chapter 1 Modeling “and if possible” and “or at least”: Different Forms of Bipolarity in Flexible Querying
Chapter 2 Constraint-Wish and Satisfied-Dissatisfied: An Overview of Two Approaches for Dealing with Bipolar Querying
Chapter 3 A Relational Algebra for Generalized Fuzzy Bipolar Conditions
Chapter 4 Bipolarity in Database Querying: Various Aspects and Interpretations

Part II Ontology-based Data Access
Chapter 5 On the Top-k Retrieval Problem for Ontology-Based Access to Databases
Chapter 6 Semantic Data Management Using Fuzzy Relational Databases

Part III Uncertain Databases
Chapter 7 Information Systems Uncertainty Design and Implementation Combining: Rough, Fuzzy, and Intuitionistic Approaches
Chapter 8 Flexible Bipolar Querying of Uncertain Data Using an Ontology
Chapter 9 Aspects of Dealing with Imperfect Data in Temporal Databases

Part IV Flexible Queries Over Nonstandard Data
Chapter 10 A Unifying Model of Flexible Queries with Distinct Semantics of Search Term Weights
Chapter 11 Social Network Database Querying Based on Computing with Words

Part V Fuzzy Knowledge Discovery and Exploitation
Chapter 12 Fuzzy Cardinalities as a Basis to Cooperative Answering
Chapter 13 Scalability and Fuzzy Systems: What Parallelization Can Do