
Knowledge Processing and Data Analysis
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Content
- Title
- Preface
- Organization
- Table of Contents
- Part I: Applications of Conceptual Structures
- Conceptual Knowledge Processing: Theory and Practice
- Conceptual Knowledge Processing
- Theory
- Practice
- Exploring
- Searching
- Recognizing
- Identification
- Investigating
- Analyzing
- Making Aware
- Deciding
- Improving
- Restructuring
- Memorizing
- Informing
- Summary
- References
- Non-symmetric Indiscernibility
- Indiscernibility
- Functional Dependencies and Indiscernibility
- Linguistic Variables
- Decision Making
- The Lattice of Rough Set Approximations
- Conclusion
- References
- Computing Graph-Based Lattices from Smallest Projections
- Introduction
- Pattern Structures on Sets of Graphs
- Analyzing Graph Datasets Using Lattice-Based Approaches
- A Top-Down Algorithm
- Top-Down and Bottom-Up Algorithms
- Conclusions
- References
- Combined Logics of Knowledge, Time, and Actions for Reasoning about Multi-agent Systems
- Introduction
- Elements of Modal Logic
- Combining Knowledge, Actions and Time
- Propositional Logic for Epistemic Agents
- Branching Temporal Logic with Actions
- Combined Logics of Knowledge, Actions, and Time
- Model Checking Problem for Combined Logics
- References
- Applications of Temporal Conceptual Semantic Systems
- Introduction
- Example: A Moving High Pressure Zone
- Basic Conceptual Notions
- The Scales of Our Example
- Conceptual Semantic Systems
- Main Ideas
- Definition of a Conceptual Semantic System
- Object Representation by Tuples of Semantic Concepts
- Views, Selections, and Traces
- Precise and Distributed Tuples
- Temporal Conceptual Semantic Systems
- States
- Life Space and Life Track
- Transitions
- The Life Space Digraph
- Particles and Waves in Temporal Conceptual Semantic Systems
- An Application of TCSS: The Behavior of a Distillation Column
- The Data of the Distillation Column
- Visualization of a Life Track in a Nested Line Diagram
- Conclusions and Future Research
- References
- Conceptual Representation of Gene Expression Processes
- Introduction
- Gene Expression Processes in Arthritic Patients
- Temporal Concept Analysis
- Data of Gene Expression Processes and Its Conceptual Representation
- Organization of the Data
- Conceptual Visualization of Data
- Conceptual Scaling
- Conceptual Time Systems with Actual Objects and a Time Relation (CTSOT)
- Conceptual Time Systems for Six Arthritic Patients
- Results
- Two Destructive Proteins and Their Antagonist
- Transcriptional Regulation of TGFB1 Effects
- Discussion
- References
- From Published Expression and Phenotype Data to Structured Knowledge: The Arabidopsis Gene Net Supplementary Database and Its Applications
- Introduction
- The Structure of the AGNS Data
- Terminological Systems
- AGNS Ontology
- Discussion of the Ontology
- Implementation of the Ontology
- Comparison with Existing Formalizations
- Functions of Terminological Systems
- Input and Processing of Data in AGNS
- Tools for Data Analysis
- Conclusion
- References
- Part II: Concept-Based Software
- How Can Ontologies Contribute to Software Development?
- Introduction
- Basic Concepts
- Analytics
- Interactive Designing
- Verbal Representation of Knowledge Bases
- Conclusions
- References
- A Comparison of Content-Based Tag Recommendations in Folksonomy Systems
- Introduction
- Social Resource Sharing and Folksonomies
- Related Work
- Tag Recommendations as Text Classification Problem
- Definition of the Problem
- Classifiers
- Evaluation Setting
- Preprocessing
- Training and Test Datasets
- Experiments
- Evaluation Settings
- Comparison of the Classifiers
- Conclusion and Outlook
- References
- Data Weeding Techniques Applied to Roget's Thesaurus
- Introduction
- Visual Reduction Techniques
- Faceting and Plain Scaling
- Pruning and Restriction
- Decomposition and General Scaling
- Data Weeding Techniques for Roget's Thesaurus
- Conclusion
- References
- Part III: Ontologies as Conceptual Structures
- Virtual Catalog: The Ontology-Based Technology for Information Retrieval
- Introduction
- Information Retrieval on the Internet
- Measures of Efficiency of Information Retrieval
- The Search for Scientific and Technical Information on the Internet
- Mathematical Basis: Model-Theoretical Approach to the Formalization of Ontologies
- Logical Means of Ontology Representation
- Model-Theoretical Approach to the Formalization of Ontologies
- Practical Realization. The Virtual Catalog
- Description of the Virtual Catalog
- Automation of the Development of Subject Domain Ontologies
- Elaboration of Virtual Catalogs for Mathematics and Information Security
- Conclusion
- References
- Ontology Development for Domains with Complicated Structures
- Introduction
- Domain Class Definition
- Defining Level of Generality of Ontologies
- Properties of Multilevel Ontologies for Domains with Complicated Structures
- Method of Developing Ontology for Domain with Complicated Structure
- Structure of Multilevel Ontology of Chemistry
- A Fragment of the Ontology of Level 4
- Using the Ontology of Fourth Level
- Distinguishing Features of This Ontology Development Method
- Intelligent Systems for Domains with Complicated Structures
- Conclusion
- References
- Technology of Ontology Building for Knowledge Portals on Humanities
- Introduction
- Requirements to Knowledge Portal Ontology
- Structure of Knowledge Portal Ontology
- Definition of Portal Ontology
- Structuring of Knowledge Portal Ontology
- Technology of Ontology Building
- Ontology Description Language
- Ontology Editor
- Features of Methodology of Ontology Building for a Knowledge Portal
- Content-Based Access to Portal Content
- Building an Ontology for Knowledge Portal on Archeology and Ethnography
- Conclusion
- References
- Methods and Technologies of Digital Historical Factography
- Introduction
- Common Information Field
- Basic Ontology
- Data Input and Editing, Information Visualization
- Conclusion
- References
- Establishment of Taxonomic Relationships in Linguistic Ontologies
- Introduction
- Criteria for Verification of Taxonomic Relationships
- Confusion of Types and Roles
- Defining Roles
- Causes of Type-Role Confusion
- Description of Roles in Thesaurus RuThes and Ontology ONST
- Confusion of Taxonomic and Instance-Class Relationships
- Confusion of Taxonomic Relationships and Part-Whole Relationships
- Confusion of Taxonomic and Origin Relationships
- Taxonomic Relationships and Clustering of Word Senses
- Conclusion
- References
- Part IV: Data Analysis
- Problems in Constructing an Empirical Theoryof Data Mining
- Introduction
- What Is an Empirical Theory?
- State-of-the-Art DM Problem
- Reference Points for Further Development
- Function of Rival Similarity
- Construction the Decision Rule (Algorithm FRiS-Stolp)
- Selection of Informative Attributes (Algorithm FRiS-GRAD)
- Construction of Classifications (Algorithm FRiS-Tax)
- Application of FRiS-Function to the Decision of Other DM tasks
- Strengthening of the Empirical DM Theory
- Conclusion
- References
- Use of the FRiS-Function for Taxonomy, Attribute Selection and Decision Rule Construction
- Introduction
- Definition of the Function of Rival Similarity
- Use of the FRiS-Function for Selecting Stolps of Classes
- FRiS-Function as Criterion for the Choice of an Informative Subset of Attributes in Problem DX
- FRiS-Function in a Taxonomy Task
- Clustering (Stage FRiS-Cluster)
- Construction of Classification (Stage FRiS-Class)
- Choice of an Optimum Number of Taxons
- FRiS-Function in Problem SX as a Criterion for Natural Classifications
- FRiS-Function in the Problem SDX
- Conclusion
- References
- Similarity Determination for Clustering Textual Documents
- Introduction
- Similarity Determination for a Set of Documents
- Methods for Documents Clustering
- Choice of the Optimal Algorithm
- Looking for the Optimum Method for Specifying the Similarity in the Set of Documents
- Conclusion
- References
- On the Problem of Prediction
- Introduction
- The Statistical Ambiguity Problem
- Inductive-Statistical Inference
- The Requirement of Maximal Specificity in Default Logic
- The Solution of the Statistical Ambiguity Problem
- Probabilistic Approximation of Empirical Theories
- Approximation of Logical Inference by Semantic Probabilistic Inference
- Laws
- The Probability of Events and Sentences
- The Probabilistic Laws on M
- Semantic Probabilistic Inference
- Probabilistic Maximally Specific Laws
- The Solution of the Statistical Ambiguity Problem
- Probabilistic Herbrand Models
- Logical Programs
- Estimations of the Probability and Conditional Probability of Requests
- Inductive Synthesis of Probabilistic Logic Programs
- Predictions Based on Semantic Probabilistic Inference
- The Relational Data Mining and Program System 'Discovery'
- References
- Visual Data Mining and Discovery in Multivariate Data Using Monotone n-D Structure
- Introduction
- Chains and Similarity Distances between Chains
- Representing and Drawing of n-D Boolean Space in 2-D
- Learning Process by Monotone Extension
- Computational Experiment
- Conclusion and Future Work
- References
- Construction of an Event Tree on the Basis of Expert Knowledge and Time Series
- Introduction
- Event Tree and Decision Tree
- Multidimensional Time Series and Decision Trees
- From Decision Trees to Event Trees
- Bayesian Criteria for Decision Tree Pruning
- Experiments
- Summary
- References
- Author Index
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