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.
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Superior document: | Lecture Notes in Computer Science Series ; v.7250 |
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Place / Publishing House: | Berlin, Heidelberg : : Springer Berlin / Heidelberg,, 2012. Ã2012. |
Year of Publication: | 2012 |
Edition: | 1st ed. |
Language: | English |
Series: | Lecture Notes in Computer Science Series
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Berthold, Michael R. Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications. 1st ed. Berlin, Heidelberg : Springer Berlin / Heidelberg, 2012. Ã2012. 1 online resource (491 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Lecture Notes in Computer Science Series ; v.7250 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. 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. Description based on publisher supplied metadata and other sources. Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. Electronic books. Print version: Berthold, Michael R. Bisociative Knowledge Discovery Berlin, Heidelberg : Springer Berlin / Heidelberg,c2012 9783642318290 ProQuest (Firm) Lecture Notes in Computer Science Series https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=6422610 Click to View |
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English |
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eBook |
author |
Berthold, Michael R. |
spellingShingle |
Berthold, Michael R. Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications. Lecture Notes in Computer Science Series ; 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. |
author_facet |
Berthold, Michael R. |
author_variant |
m r b mr mrb |
author_sort |
Berthold, Michael R. |
title |
Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications. |
title_sub |
An Introduction to Concept, Algorithms, Tools, and Applications. |
title_full |
Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications. |
title_fullStr |
Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications. |
title_full_unstemmed |
Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications. |
title_auth |
Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications. |
title_new |
Bisociative Knowledge Discovery : |
title_sort |
bisociative knowledge discovery : an introduction to concept, algorithms, tools, and applications. |
series |
Lecture Notes in Computer Science Series ; |
series2 |
Lecture Notes in Computer Science Series ; |
publisher |
Springer Berlin / Heidelberg, |
publishDate |
2012 |
physical |
1 online resource (491 pages) |
edition |
1st ed. |
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. |
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9783642318306 9783642318290 |
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Electronic books. |
genre_facet |
Electronic books. |
url |
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illustrated |
Not Illustrated |
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000 - Computer science, information & general works |
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000 - Computer science, knowledge & systems |
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006 - Special computer methods |
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tag="040" ind1=" " ind2=" "><subfield code="a">MiAaPQ</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">MiAaPQ</subfield><subfield code="d">MiAaPQ</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">Q334-342</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3/12</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Berthold, Michael R.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Bisociative Knowledge Discovery :</subfield><subfield code="b">An Introduction to Concept, Algorithms, Tools, and Applications.</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Berlin, Heidelberg :</subfield><subfield code="b">Springer Berlin / Heidelberg,</subfield><subfield code="c">2012.</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">Ã2012.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (491 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Lecture Notes in Computer Science Series ;</subfield><subfield code="v">v.7250</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">The Future of Bisociative Reasoning and Cross-Context Data Mining.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources.</subfield></datafield><datafield tag="590" ind1=" " ind2=" "><subfield code="a">Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. </subfield></datafield><datafield tag="655" ind1=" " ind2="4"><subfield code="a">Electronic books.</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version:</subfield><subfield code="a">Berthold, Michael R.</subfield><subfield code="t">Bisociative Knowledge Discovery</subfield><subfield code="d">Berlin, Heidelberg : Springer Berlin / Heidelberg,c2012</subfield><subfield code="z">9783642318290</subfield></datafield><datafield tag="797" ind1="2" ind2=" "><subfield code="a">ProQuest (Firm)</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Lecture Notes in Computer Science Series</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=6422610</subfield><subfield code="z">Click to View</subfield></datafield></record></collection> |