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Conceptual Structures: Knowledge Architectures for Smart Applications

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Cover of 'Conceptual Structures: Knowledge Architectures for Smart Applications'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to Conceptual Graphs
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    Chapter 2 Trikonic Inter-Enterprise Architectonic
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    Chapter 3 Hypermedia Discourse: Contesting Networks of Ideas and Arguments
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    Chapter 4 Dynamic Epistemic Logic and Knowledge Puzzles
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    Chapter 5 Peirce on Icons and Cognition
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    Chapter 6 Using Cognitive Archetypes and Conceptual Graphs to Model Dynamic Phenomena in Spatial Environments
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    Chapter 7 A Datatype Extension for Simple Conceptual Graphs and Conceptual Graphs Rules
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    Chapter 8 A Knowledge Management Optimization Problem Using Marginal Utility in a Metric Space with Conceptual Graphs
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    Chapter 9 Conceptual Graphs as Cooperative Formalism to Build and Validate a Domain Expertise
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    Chapter 10 An Inferential Approach to the Generation of Referring Expressions
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    Chapter 11 A Conceptual Graph Description of Medical Data for Brain Tumour Classification
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    Chapter 12 A Conceptual Graph Based Approach to Ontology Similarity Measure
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    Chapter 13 A Comparison of Different Conceptual Structures Projection Algorithms
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    Chapter 14 A Conceptual Graph Approach to Feature Modeling
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    Chapter 15 From Conceptual Structures to Semantic Interoperability of Content
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    Chapter 16 Faster Concept Analysis
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    Chapter 17 The Design Space of Information Presentation: Formal Design Space Analysis with FCA and Semiotics
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    Chapter 18 Reducing the Representation Complexity of Lattice-Based Taxonomies
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    Chapter 19 An FCA Perspective on n -Distributivity
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    Chapter 20 Towards a Semantology of Music
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    Chapter 21 Analysis of the Publication Sharing Behaviour in BibSonomy
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    Chapter 22 The MILL – Method for Informal Learning Logistics
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    Chapter 23 Bilingual Word Association Networks
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    Chapter 24 Using FCA for Encoding Closure Operators into Neural Networks
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    Chapter 25 Arc Consistency Projection: A New Generalization Relation for Graphs
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    Chapter 26 Mining Frequent Closed Unordered Trees Through Natural Representations
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    Chapter 27 Conceptual Structures: Knowledge Architectures for Smart Applications
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    Chapter 28 Historical and Conceptual Foundation of Diagrammatical Ontology
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    Chapter 29 Learning Common Outcomes of Communicative Actions Represented by Labeled Graphs
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    Chapter 30 Belief Flow in Assertion Networks
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    Chapter 31 Conceptual Fingerprints: Lexical Decomposition by Means of Frames – a Neuro-cognitive Model
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    Chapter 32 Constants and Functions in Peirce’s Existential Graphs
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    Chapter 33 Revelator Game of Inquiry: A Peircean Challenge for Conceptual Structures in Application and Evolution
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    Chapter 34 Helping System Users to Be Smarter by Representing Logic in Transaction Frame Diagrams
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    Chapter 35 Quo Vadis, CS? – On the (non)-Impact of Conceptual Structures on the Semantic Web
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    Chapter 36 A Framework for Analyzing and Testing Overlapping Requirements with Actors in Conceptual Graphs
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    Chapter 37 Implementation of SPARQL Query Language Based on Graph Homomorphism
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    Chapter 38 Cooperative CG-Wrappers for Web Content Extraction
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    Chapter 39 Conceptual Graphs and Ontologies for Information Retrieval
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    Chapter 40 Representation Levels Within Knowledge Representation
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    Chapter 41 Supporting Lexical Ontology Learning by Relational Exploration
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    Chapter 42 Characterizing Implications of Injective Partial Orders
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    Chapter 43 DVDSleuth: A Case Study in Applied Formal Concept Analysis for Navigating Web Catalogs
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    Chapter 44 Navigation in Knowledge-Based System for Helpdesk Based on FCA
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    Chapter 45 Functorial Properties of Formal Concept Analysis
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    Chapter 46 Towards an Ontology to Conceptualize Solution Analysis Tasks in CSCL Environments
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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