Knowledge Processing and Data Analysis
First International Conference, KONT 2007, Novosibirsk, Russia, September 14-16, 2007,and First International Conference, KPP 2007, Darmstadt, Germany, September 28-30, 2007. Revised Selected Papers
Published on 28. July 2011
XVI, 321 pages
978-3-642-22140-8 (ISBN)
Description
This book constitutes the proceedings of the First International Conference on Knowledge - Ontology - Theory (KONT 2007) held in Novosibirsk, Russia, in September 2007 and the First International Conference on Knowledge Processing in Practice (KPP 2007) held in Darmstadt, Germany, in September 2007. The 21 revised full papers were carefully reviewed and selected from numerous submissions and cover four main focus areas: applications of conceptual structures; concept based software; ontologies as conceptual structures; and data analysis.
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Karl Erich Wolff | Dmitry E. Palchunov | Nikolay G. Zagoruiko
Knowledge Processing and Data Analysis
First International Conference, KONT 2007, Novosibirsk, Russia, September 14-16, 2007,and First International Conference, KPP 2007, Darmstadt, Germany, September 28-30, 2007. Revised Selected Papers
Book
07/2011
Springer
€53.49
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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
