Quantum-like models for information retrieval and decision-making. ([2019])
- Record Type:
- Book
- Title:
- Quantum-like models for information retrieval and decision-making. ([2019])
- Main Title:
- Quantum-like models for information retrieval and decision-making
- Further Information:
- Note: Diederik Aerts, Andrei Khrennikov, Massimo Melucci, Bourama Toni, editors.
- Editors:
- Aerts, Diederik, 1953-
Khrennikov, A. I︠U︡ (Andreĭ I︠U︡rʹevich), 1958-
Melucci, Massimo
Toni, Bourama - Contents:
- Intro; Preface; Contents; Contributors; Modeling Meaning Associated with Documental Entities: Introducing the Brussels Quantum Approach; 1 Introduction; 2 The Double-Slit Experiment; 3 Interrogative Processes; 4 Modeling the QWeb; 5 Adding Context; 6 Conclusion; Appendix 1: Interference Plus Context Effects; Appendix 2: Meaning Bond; References; Non-separability Effects in Cognitive Semantic Retrieving; 1 Introduction; 2 Bell Test in the Problem of Cognitive Semantic Information Retrieval; 2.1 Bell Inequality and Its Interpretation; 2.2 Bell Test in Semantic Retrieving; 3 Results; References Introduction to Hilbert Space Multi-Dimensional Modeling1 Introduction; 2 Basics of Quantum Probability Theory; 3 Steps to Build an HSM Model; 3.1 How to Determine the Compatibility Relations; 3.2 How to Determine the Dimension; 3.3 Define the Initial State; 3.4 Define the Projectors; 3.5 Compute the Choice Probabilities; 3.6 Estimate Model Parameters, Compare and Test Models; 4 Computer Programs; 5 Concluding Comments; References; Basics of Quantum Theory for Quantum-Like Modeling Information Retrieval; 1 Introduction; 2 Kolmogorov's Axiomatics of Classical Probability; 3 Quantum Mathematics 3.1 Hermitian Operators in Hilbert Space3.2 Pure and Mixed States: Normalized Vectors and Density Operators; 4 Quantum Mechanics: Postulates; 5 Compatible and Incompatible Observables; 5.1 Post-Measurement State From the Projection Postulate; 6 Interpretations of Quantum Mechanics; 6.1 Ensemble andIntro; Preface; Contents; Contributors; Modeling Meaning Associated with Documental Entities: Introducing the Brussels Quantum Approach; 1 Introduction; 2 The Double-Slit Experiment; 3 Interrogative Processes; 4 Modeling the QWeb; 5 Adding Context; 6 Conclusion; Appendix 1: Interference Plus Context Effects; Appendix 2: Meaning Bond; References; Non-separability Effects in Cognitive Semantic Retrieving; 1 Introduction; 2 Bell Test in the Problem of Cognitive Semantic Information Retrieval; 2.1 Bell Inequality and Its Interpretation; 2.2 Bell Test in Semantic Retrieving; 3 Results; References Introduction to Hilbert Space Multi-Dimensional Modeling1 Introduction; 2 Basics of Quantum Probability Theory; 3 Steps to Build an HSM Model; 3.1 How to Determine the Compatibility Relations; 3.2 How to Determine the Dimension; 3.3 Define the Initial State; 3.4 Define the Projectors; 3.5 Compute the Choice Probabilities; 3.6 Estimate Model Parameters, Compare and Test Models; 4 Computer Programs; 5 Concluding Comments; References; Basics of Quantum Theory for Quantum-Like Modeling Information Retrieval; 1 Introduction; 2 Kolmogorov's Axiomatics of Classical Probability; 3 Quantum Mathematics 3.1 Hermitian Operators in Hilbert Space3.2 Pure and Mixed States: Normalized Vectors and Density Operators; 4 Quantum Mechanics: Postulates; 5 Compatible and Incompatible Observables; 5.1 Post-Measurement State From the Projection Postulate; 6 Interpretations of Quantum Mechanics; 6.1 Ensemble and Individual Interpretations; 6.2 Information Interpretations; 7 Quantum Conditional (Transition) Probability; 8 Observables with Nondegenerate Spectra: Double-Stochasticity of the Matrix of Transition Probabilities; 9 Formula of Total Probability with the Interference Term 9.1 Växjö (Realist Ensemble Contextual) Interpretation of Quantum Mechanics10 Quantum Logic; 11 Space of Square Integrable Functions as a State Space; 12 Operation of Tensor Product; 13 Ket- and Bra-Vectors: Dirac's Symbolism; 14 Qubit; 15 Entanglement; 16 Violation of Formula of Total Probability in Two-Slit Experiment; References; Representing Words in Vector Space and Beyond; 1 Introduction; 2 Background; 2.1 Distributional Hypothesis; 2.2 A Brief History of Word Embedding; 3 Applications of Word Embedding; 3.1 Word-Level Applications; 3.2 Sentence-Level Application 3.3 Sentence-Pair Level Application3.4 Seq2seq Application; 3.5 Evaluation; 4 Reconsidering Word Embedding; 4.1 Limitations; 4.2 Trends; 4.3 Linking Word Embedding to Vector-Space Based Approaches and Representation of Thematic Structures; 4.4 Towards Dynamic Word Embedding; 5 Conclusion; References; Quantum-Based Modelling of Database States; 1 Introduction; 2 Motivating Example: Car Dealership; 3 Modelling Elementary Data Types; 3.1 Orthogonal Data Types; 3.2 Non-orthogonal Data Types; 4 Data Type Construction; 5 Quantum-Based Data Type Constructors; 5.1 Tuple Data Type Constructor; 5.2 Set Data Type Constructor … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2019
- Extent:
- 1 online resource
- Subjects:
- 025.524
Information retrieval -- Data processing
Decision making -- Data processing
Decision making -- Data processing
Information retrieval -- Data processing
Electronic books - Languages:
- English
- ISBNs:
- 9783030259136
3030259137 - Notes:
- Note: Includes bibliographical references
Note: Online resource; title from PDF title page (SpringerLink, viewed October 31, 2019). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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- Physical Locations:
- British Library HMNTS - ELD.DS.455320
- Ingest File:
- 02_592.xml