Contents -- Preface -- 1. Introduction -- 1.1 Document Retrieval -- 1.2 Intelligent Information Access -- 1.3 Recent Trends -- 1.3.1 Object Retrieval -- 1.3.2 Web 2.0 . -- 1.3.3 Semantic Web -- 1.4 The Role of Time and Space -- 1.5 Overview -- 2. Preliminaries from Fuzzy Set Theory -- 2.1 Vagueness -- 2.2 Fuzzy Logic Connectives -- 2.3 Fuzzy Sets -- 2.3.1 Definitions -- 2.3.2 Fuzzy Sets in R -- 2.4 Fuzzy Relations -- 2.5 Criticism of Fuzzy Set Theory -- 3. Relatedness of Fuzzy Sets -- 3.1 Introduction -- 3.2 Definition -- 3.3 Properties -- 3.3.1 Basic Properties -- 3.3.2 Interaction -- 3.3.3 Transitivity -- 3.4 Proof of the Transitivity Table -- 4. Representing Fuzzy Temporal Information -- 4.1 Introduction -- 4.2 Temporal Relations -- 4.2.1 Crisp Temporal Relations -- 4.2.2 Fuzzification of Temporal Relations -- 4.3 Definitions Based on Relatedness Measures -- 4.3.1 Generalizing Constraints between Boundary Points -- 4.3.2 The Case for the Lukasiewicz Connectives -- 4.3.3 Fuzzy Allen Relations -- 4.4 Properties -- 4.4.1 Properties of the Generalized Boundary Constraints -- 4.4.2 Properties of the Fuzzy Allen Relations -- 4.4.2.1 Basic properties -- 4.4.2.2 Transitivity -- 4.5 Evaluating the Fuzzy Temporal Relations -- 4.5.1 Characterization for Linear Fuzzy Sets -- 4.5.1.1 Evaluating be ( ), be ( ), eb ( ) and eb ( ) -- 4.5.1.2 Evaluating bb ( ), bb ( ), ee ( ) and ee( ) -- 4.5.2 Characterization for Piecewise Linear Fuzzy Time Intervals -- 4.5.3 Alternative Characterizations for = 0 -- 5. Reasoning about Fuzzy Temporal Information -- 5.1 Introduction -- 5.2 Temporal Reasoning -- 5.3 Complete Reasoning about Fuzzy Time Spans -- 5.3.1 FI-Satis ability -- 5.3.2 Computational Complexity -- 5.3.3 Entailment -- 5.3.4 Implementation of a Fuzzy Temporal Reasoner -- 5.3.4.1 Optimized backtracking.

5.3.4.2 Experimental evaluation -- 5.4 Efficient Reasoning about Fuzzy Time Spans -- 5.4.1 2-Consistency -- 5.4.2 Transitivity of Fuzzy Temporal Relations -- 5.4.3 Experimental Results -- 6. Event-based Information Retrieval -- 6.1 Introduction -- 6.2 Temporal Information Extraction -- 6.3 Extracting Time spans -- 6.3.1 Crisp Time Spans -- 6.3.2 Fuzzy Time Spans -- 6.3.2.1 Inconsistent dates -- 6.3.2.2 Underspeci ed dates -- 6.3.2.3 Con dence scores -- 6.4 Extracting Qualitative Relations -- 6.4.1 Co-occurring Dates -- 6.4.1.1 Before -- 6.4.1.2 During -- 6.4.2 Document Structure -- 6.4.2.1 Before -- 6.4.2.2 During -- 6.5 Fuzzy Temporal Reasoning -- 6.5.1 Constructing a Knowledge Base -- 6.5.2 Reasoning -- 6.5.3 Event Retrieval -- 6.6 Experimental Results -- 7. Representing Fuzzy Spatial Information -- 7.1 Introduction -- 7.2 Spatial Relations -- 7.2.1 Crisp Spatial Relations -- 7.2.2 Fuzzification of Spatial Relations -- 7.3 Definitions Based on Relatedness Measures -- 7.3.1 Fuzzy Spatial Relations between Points -- 7.3.2 Fuzzy Spatial Relations between Vague Regions -- 7.3.3 Composing Fuzzy Spatial Relations -- 7.4 Fuzzifying the RCC -- 7.4.1 Fuzzy RCC Relations -- 7.4.2 Properties -- 7.4.3 Transitivity -- 7.5 Interpretation of Fuzzy RCC Relations -- 7.5.1 Resemblance Relations -- 7.5.2 Semantics of the Fuzzy RCC Relations -- 8. Reasoning about Fuzzy Spatial Information -- 8.1 Introduction -- 8.2 Spatial Reasoning -- 8.3 Satis ability of Fuzzy Topological Information -- 8.3.1 Definitions -- 8.3.2 Satis ability -- 8.3.2.1 Normalised sets -- 8.3.2.2 Standard sets of fuzzy RCC formulas -- 8.3.2.3 Computational complexity -- 8.3.3 Other Reasoning Tasks -- 8.3.3.1 Entailment -- 8.3.3.2 Best Truth{Value Bound -- 8.3.3.3 Inconsistency repairing -- 8.4 Properties -- 8.4.1 Reduction to the RCC -- 8.4.2 Relationship with the Egg-Yolk Calculus.

8.4.3 Realizability in Any Dimension -- 9. Geographic Information Retrieval -- 9.1 Introduction -- 9.2 Acquisition of Geographical Knowledge -- 9.3 Location Approximation and Local Search -- 9.3.1 Collecting Data -- 9.3.2 Representing Vague Geographical Information -- 9.3.2.1 Fuzzy nearness relations -- 9.3.2.2 Representing named nearness relations -- 9.3.2.3 Representing quanti ed nearness relations -- 9.3.2.4 Representing neighbourhoods -- 9.3.3 Location Approximation -- 9.3.4 Experimental Results -- 9.3.4.1 Location approximation -- 9.3.4.2 Local search -- 9.4 Establishing Fuzzy Footprints -- 9.4.1 Weighting the Input Data -- 9.4.2 Defining Neighbourhoods -- 9.4.3 Analyzing the Fuzzy Footprints -- 9.4.4 Experimental Results -- 9.5 Modelling the Neighbourhoods of Cardi : A Case Study -- 9.5.1 Containment Relations -- 9.5.2 Adjacency Relations -- 9.5.3 Fuzzy Spatial Reasoning -- Conclusions -- Appendix A Proof of Proposition 5.9 -- Appendix B Proof of Proposition 5.10 -- B.1 1 = 2 = 0 -- B.1.1 Restrictions for be (A -- C) and eb (A -- C) -- B.1.2 Restrictions for bb (A -- C) and ee (A -- C) -- B.2 1 = 0 -- 2 > 0 -- B.2.1 Restriction for be (A -- C) -- B.2.1.1 Assuming 1 -- B.2.1.2 Assuming 1 -- B.2.1.3 Assuming 1 -- B.2.2 Restrictions for bb (A -- C) and ee (A -- C) -- B.2.2.1 Assuming 1 + TW( 1, 2) 1 + TW( 1, 2) -- B.2.2.2 Assuming 1 + TW( 1, 2) 0, 2 = 0 -- B.3.1 Restriction for be (A -- C) -- B.3.1.1 Assuming 1 -- B.3.1.2 Assuming 1 -- B.3.2 Restrictions for bb4(A -- C) and ee4(A -- C) -- B.3.2.1 Assuming 2 + TW( 1 -- 2) 2 + TW( 1 -- 2) -- B.3.3 Restriction for eb4(A -- C) -- B.4 1 > 0, 2 > 0 -- B.4.1 Restrictions for bb (A -- C) and ee (A -- C) -- B.4.2 Restrictions for be (A -- C) and eb (A -- C) -- Appendix C Proof of Proposition 8.1 -- C.1 Lemmas.

C.2 Connection -- C.3 Overlap -- C.4 Part of -- C.5 Non-Tangential Part of -- Bibliography -- Index.