Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications.
The focus of this book, and the BISON project from which the contributions originate, is a network based integration of data repositories of a variety of types, and the development of new ways to analyse and explore the resulting gigantic information networks.
| Main Author: | |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg :
Springer Berlin / Heidelberg,
2012.
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| Edition: | 1st ed. |
| Series: | Lecture Notes in Computer Science Series
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| Subjects: | |
| Online Access: | Click to View |
Table of Contents:
- Title
- Foreword
- Table of Contents
- Part I: Bisociation
- Towards Bisociative Knowledge Discovery
- Motivation
- Bisociation
- Types of Bisociation
- Bridging Concepts
- Bridging Graphs
- Bridging by Structural Similarity
- Other Types of Bisociation
- Bisociation Discovery Methods
- Future Directions
- Conclusions
- References
- Towards Creative Information Exploration Based on Koestler's Concept of Bisociation
- Introduction
- Creativity
- What Is Creativity?
- Three Roads to Creativity
- Computational Creativity
- Koestler's Concept of Bisociation
- Elements of Bisociative Computational Creativity
- Towards a Formal Definition of Bisociation
- Related Work
- Discussion and Conclusion
- References
- From Information Networks to Bisociative Information Networks
- Introduction
- Different Categories of Information Network
- Properties of Information Units
- Properties of Relations
- Prominent Types of Information Networks
- Ontologies
- Semantic Networks
- Topic Maps
- Weighted Networks
- BisoNets: Bisociative Information Networks
- Summary
- Patterns of Bisociation in BisoNets
- Bridging Concept
- Bridging Graphs
- Bridging by Graph Similarity
- Conclusion
- References
- Part II: Representation and Network Creation
- Network Creation: Overview
- References
- Selecting the Links in BisoNets Generated from Document Collections
- Introduction
- Reminder: Bisociation and BisoNets
- BisoNet Generation
- Data Access and Pre-processing
- Creating Nodes
- Linking Nodes: Different Metrics
- Cosine and Tanimoto Measures
- The Bison Measure
- The Probabilistic Measure
- Benchmarks
- The Swanson Benchmark
- The Biology and Music Benchmark
- Conclusion
- References
- Bridging Concept Identification for Constructing Information Networks from Text Documents
- Introduction.
- Problem Description
- Document Acquisition and Preprocessing
- Document Acquisition
- Document Preprocessing
- Background Knowledge
- Candidate Concept Detection
- Distance Measures between Vectors
- Identifying Bridging Concept Candidates for High Quality Network Entities Extraction
- Heuristics Description
- Frequency Based Heuristics
- Tf-idf Based Heuristics
- Similarity Based Heuristics
- Outlier Based Heuristics
- Baseline Heuristics
- Heuristics Evaluation
- Evaluation Procedure
- Migraine-Magnesium Dataset
- Comparison of the Heuristics
- Network Creation
- References
- Discovery of Novel Term Associations in a Document Collection
- Introduction
- Related Work
- The tpf-idf-tpu Model of Important Term Pair Associations
- Term Pair Frequency (tpf) and Inverse Document Frequency (idf)
- Term Pair Uncorrelation (tpu)
- Experiments
- Tpf-idf-tpu vs. tf-idf
- Sentence vs. Document-Level tpf-idf-tpu Methods
- Comparison of tpf-idf-tpu and tf-idf Using Annotated Test Set
- Conclusion
- References
- Cover Similarity Based Item Set Mining
- Introduction
- Frequent Item Set Mining
- Jaccard Item Sets
- The Eclat Algorithm
- The JIM Algorithm (Jaccard Item Set Mining)
- Other Similarity Measures
- Experiments
- Conclusions
- References
- Patterns and Logic for Reasoning with Networks
- Introduction
- The Biomine and ProbLog Frameworks
- Using Graphs: Biomine
- Using Logic: ProbLog
- Summary
- Inference and Reasoning Techniques
- Deduction: Reasoning about Node Tuples
- Abduction: Reasoning about Subgraphs
- Induction: Finding Patterns
- Combining Induction and Deduction
- Modifying the Knowledge Base
- Summary
- Using Probabilistic or Algebraic Labels
- The Probabilistic Model of Biomine and ProbLog
- Probabilistic Deduction
- Probabilistic Abduction and Top-k Instantiations.
- Patterns and Probabilities
- Combining Induction and Deduction
- Modifying the Probabilistic Knowledge Base
- Beyond Probabilities
- Conclusions
- References
- Part III: Network Analysis
- Network Analysis: Overview
- References
- BiQL: A Query Language for Analyzing Information Networks
- Introduction
- Motivating Example
- Requirements
- Data Representation
- Basic Data Manipulation
- Illustrative Examples
- Related Work
- Knowledge Discovery
- Databases
- Conclusions
- References
- Review of BisoNet Abstraction Techniques
- Introduction
- Preference-Free Methods
- Relative Neighborhood Graph
- Node Centrality
- PageRank and HITS
- Birnbaum's Component Importance
- Graph Partitioning
- Hierarchical Clustering
- Edge Betweenness
- Frequent Subgraphs
- Preference-Dependent Methods
- Relevant Subgraph Extraction
- Detecting Interesting Nodes or Paths
- Personalized PageRank
- Exact Subgraph Search
- Similarity Subgraph Search
- Conclusion
- References
- Simplification of Networks by Edge Pruning
- Introduction
- Lossy Network Simplification
- Definitions
- Example Instances of the Framework
- Analysis of the Problem
- Multiplicativity of Ratio of Connectivity Kept
- A Bound on the Ratio of Connectivity Kept
- A Further Bound on the Ratio of Connectivity Kept
- Algorithms
- Naive Approach
- Brute Force Approach
- Path Simplification
- Combinational Approach
- Experiments
- Experimental Setup
- Results
- Related Work
- Conclusion
- References
- Network Compression by Node and Edge Mergers
- Introduction
- Problem Definition
- Weighted and Compressed Graphs
- Simple Weighted Graph Compression
- Generalized Weighted Graph Compression
- Optimal Superedge Weights and Mergers
- Bounds for Distances between Graphs
- A Bound on Distances between Nodes
- Related Work
- Algorithms.
- Experiments
- Experimental Setup
- Results
- Conclusions
- References
- Finding Representative Nodes in Probabilistic Graphs
- Introduction
- Related Work
- Similarities in Probabilistic Graphs
- Clustering and Representatives in Graphs
- Experiments
- Test Setting
- Results
- Conclusions
- References
- (Missing) Concept Discovery in Heterogeneous Information Networks
- Introduction
- Bisociative Information Networks
- Concept Graphs
- Preliminaries
- Detection
- Application
- Results
- Conclusion and Future work
- References
- Node Similarities from Spreading Activation
- Introduction
- Related Work
- Spreading Activation
- Linear Standard Scenario
- Node Signatures
- Node Similarities
- Activation Similarity
- Signature Similarity
- Experiments
- Schools-Wikipedia
- Conclusion
- References
- Towards Discovery of Subgraph Bisociations
- Motivation
- Networks, Domains and Bisociations
- Knowledge Modeling
- Domains
- Bisociations
- Finding and Assessing Bisociations
- Domain Extraction
- Scoring Bisociation Candidates
- Complexity and Scalability
- Preliminary Evaluation
- Related Work
- Conclusion
- References
- Part IV: Exploration
- Exploration: Overview
- Introduction
- Contributions
- Conclusions
- References
- Data Exploration for Bisociative Knowledge Discovery: A Brief Overview of Tools and Evaluation Methods
- Introduction
- Bisociative Data Exploration
- Different Meanings of Exploration
- Definition of Bisociative Exploration
- Implications for User Interface Design
- Supporting Bisociative Data Exploration
- Tools for Data Exploration
- Evaluation of Knowledge Discovery Tools
- Evaluation Challenges
- Open Issues
- Benchmark Evaluation for Discovery Tools
- Conclusion and Future Work
- References.
- On the Integration of Graph Exploration and Data Analysis: The Creative Exploration Toolkit
- Introduction
- State of the Art in Graph Interaction and Visualization
- The Creative Exploration Toolkit
- Network and Algorithm Providers
- Communication between CET and Other Tools
- The KNIME Information Mining Platform
- Wikipedia
- Evaluation
- Study Design
- Results of the Study
- Conclusion and Future Work
- References
- Bisociative Knowledge Discovery by Literature Outlier Detection
- Introduction
- Related Work in Literature Mining
- The Upgraded RaJoLink Knowledge Discovery Process
- Outlier Detection in the RaJoLink Knowledge Discovery Process
- Application of Outlier Detection in the Autism Literature
- Conclusions
- References
- Exploring the Power of Outliers for Cross-Domain Literature Mining
- Introduction
- Related Work
- Experimental Datasets
- Detecting Outlier Documents
- Classification Noise Filters for Outlier Detection
- Experimental Evaluation
- Conclusions
- References
- Bisociative Literature Mining by Ensemble Heuristics
- Introduction
- Problem Description
- Methodology for Bridging Concept Identification and Ranking
- Base Heuristics
- Ensemble Heuristic
- Evaluation of the Methodology
- Experimental Setting
- Results in the Migraine-Magnesium Dataset
- Results in Autism-Calcineurin Dataset
- The CrossBee System
- A Typical Use Case
- Other CrossBee Functionalities
- Discussion and Further Work
- References
- Part V: Applications and Evaluation
- Applications and Evaluation: Overview
- Introduction
- Contributions
- Lessons Learned
- The BISON Software for Applications Development
- Application Potential of the BISON Methodology
- Evaluation of the BISON Methodology and the Potential for Triggering Creativity.
- The Future of Bisociative Reasoning and Cross-Context Data Mining.