Uncertainty Management in Information Systems

1 Introduction.- 1 Scope.- 2 Structure.- 2 Sources of Uncertainty, Imprecision, and Inconsistency in Information Systems.- 1 Introduction.- 2 Imperfect Descriptions: Classification.- 3 Imperfect Descriptions: Solutions.- 4 Imperfect Manipulation and Processing.- 5 Challenges.- 3 Imperfect Information in Relational Databases.- 1 Introduction.- 2 Possible Worlds.- 3 Manipulating an Imperfect Database.- 4 Existential Values.- 5 Inexistent Values.- 6 Open Databases and Null Values.- 7 Combination of Null Values.- 8 Universal Relation Databases and Null Values.- 9 Null Values in Nested Relational Databases.- 10 Maybe Tuples.- 11 Disjunctive Databases.- 12 Probabilistic Databases.- 4 Uncertainty in Intelligent Databases.- 1 Introduction.- 2 Incompleteness.- 3 Validity.- 4 Conclusion.- 5 Uncertain, Incomplete, and Inconsistent Data in Scientific and Statistical Databases.- 1 Introduction.- 2 Sources of Uncertainty.- 3 Example Databases.- 4 Database Error Controls.- 5 Data Accuracy and Database Performance.- 6 Missing Categorical Data.- 7 Conclusions.- 6 Knowledge Discovery and Acquisition from Imperfect Information.- 1 Introduction.- 2 Uncertainty Management.- 3 Knowledge Discovery in Databases.- 4 Knowledge Acquisition.- 5 Sources of Imperfection in Discovered Patterns.- 6 Summary.- 7 Uncertainty In Information Retrieval Systems.- 1 Introduction.- 2 Background.- 3 Principal Retrieval Models.- 4 Current Trends in Information Retrieval.- 5 Open Problems.- 8 Imperfect Information: Imprecision and Uncertainty.- 1 Imperfect Information.- 2 Varieties of Imperfect Information.- 3 Modeling.- 4 Combining Models of Ignorance.- 5 Conclusion.- Appendix A: A Structured Thesaurus of Imperfection.- Appendix B: Thesaurus on Uncertainty and Incompleteness.- Appendix C: Models for Uncertaintyon Finite Frames.- 9 Probabilistic and Bayesian Representations of Uncertainty in Information Systems: a Pragmatic Introduction.- 1 Introduction and Overview.- 2 Basic Issues in Bayesian Probability.- 3 Probabilistic Representations of Alternative Types of Uncertainty.- 4 Example Problems and Their Bayesian Solutions.- 5 Representing Uncertainty in Large Databases.- 6 Conclusions.- 10 An Introduction to the Fuzzy Set and Possibility Theory-Based Treatment of Flexible Queries and Uncertain or Imprecise Databases.- 1 Introduction.- 2 Imperfect Information: Vocabulary.- 3 Fuzzy Databases.- 4 Flexible Queries.- 5 Imperfect Data in a Database.- 6 Integrity Constraints and Fuzzy Functional Dependencies.- 7 Concluding Remarks.- 11 Logical Handling of Inconsistent and Default Information.- 1 Introduction.- 2 Handling Inconsistent Information.- 3 Handling Default Information.- 4 Labeled Deductive Systems for Practical Reasoning.- 5 Conclusions.- 12 The Transferable Belief Model for Belief Representation.- 1 Introduction.- 2 The Transferable Belief Model.- 3 The Mathematics of the TBM.- 4 Applications to Databases.- 5 Application with Sources Reliability.- 6 Application for Diagnosis.- 7 Conclusions.- 13 Approximate Reasoning Systems: Handling Uncertainty and Imprecision in Information Systems.- 1 Introduction.- 2 Probabilistic Approaches.- 3 Fuzzy Logic Based Approaches.- 4 Conclusions.- 14 On the Classification of Uncertainty Techniques in Relation to the Application Needs.- 1 Introduction.- 2 On the Classification of Uncertainty Techniques.- 3 On Sources of Uncertainty.- 4 Building Applications with Uncertainty Management.- 5 Conclusions.- 15 A Bibliography on Uncertainty Management in Information Systems.- 1 Introduction.- 2 Surveys.- 3 Null Values.- 4 Logic.- 5 Fuzzy Set andPossibility Theory.- 6 Probability Theory.- 7 Query-level Uncertainty.- 8 Schema-level Uncertainty.- 9 Complexity Analyses.- 10 Miscellaneous.