Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Advances in chance discovery : extended selection from international workshops / / Yukio Ohsawa and Akinori Abe (eds.)
| Advances in chance discovery : extended selection from international workshops / / Yukio Ohsawa and Akinori Abe (eds.) |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2013 |
| Descrizione fisica | 1 online resource (XIV, 250 p.) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
AbeAkinori
OhsawaY <1968-> (Yukio) |
| Collana | Studies in computational intelligence |
| Soggetto topico |
Data mining
Decision making - Data processing |
| ISBN | 3-642-30114-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cognition and Communication toward Chance Discovery -- Curation and Communication in Chance Discovery -- Turning Down a Chance: An Argument From Simplicity -- A Chance Favors a Prepared Mind: Chance Discovery from Cognitive Psychology -- Data Visualization as Chance Curation -- Chance Discovery with Self-Organizing Maps: Discovering Imbalances in Financial Networks -- Map Interface for a Text Data Set by Recursive Clustering -- Multimodal Discussion Analysis based on Temporal Sequence -- Framework of early adopters roaming among tribes for discovering innovative creation -- Data-Driven Innovation Technologies for Smarter Business from Innovators’ Market Game to iChance Creativity Support System -- Computational and Logical Cutting Edges for Analysis and Synthesis of Data -- Paired Evaluators Method to Track Concept Drift: An Application in Finance -- Efficient Service Discovery Among Heterogeneous Agents Using a Novel Agent Ranking Algorithm -- Discovering Chances for Health Problems and Falls in the Elderly using Data Mining Approach -- Temporal Logics Modeling Logical Uncertainty, Local and Global Chance Discovery -- Discovering Probabilistic Models of Pilot Behavior from Aircraft Telemetry Data -- Constructing Feature Set by using Temporal Clustering of Term Usages in Document Categorization -- Finding Rare Patterns with Weak Correlation Constraint: Progress in Indicative and Chance Patterns. |
| Record Nr. | UNINA-9910437914303321 |
| Berlin ; ; New York, : Springer, c2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Tools for activating data marketplace : toward innovations with data-mediated communications / / Teruaki Hayashi, Yukio Ohsawa
| Tools for activating data marketplace : toward innovations with data-mediated communications / / Teruaki Hayashi, Yukio Ohsawa |
| Autore | Hayashi Teruaki |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (247 pages) |
| Disciplina | 005.7 |
| Collana | Contributions to international relations |
| Soggetto topico |
Big data
Data mining - Economic aspects Instructional and educational works |
| ISBN | 3-031-06145-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgments -- Contents -- Chapter 1: Introduction: Why A Market of Data? A Solution for Innovations -- 1.1 Data: Have We Got It Right? -- 1.2 Data Marketplace: A Platform for Value Exchange and Innovation -- 1.3 Interactions of Stakeholders in Markets: Are They Toward Innovations? -- 1.4 Organization of This Book -- References -- Chapter 2: Data-Interactive Innovations as the Heart of Market of Data (MoDAT) -- 2.1 Innovation as a Process of Trans-Dimensional Communication -- 2.2 Three Reasons for Asking Why and How -- 2.2.1 Reason 1: Data-Interactive Innovation as Design Communication -- 2.2.2 Reason 2: Design Communication Requires Two Kinds of Questions -- Divergent-Convergent Inquiry-Based Design Thinking Model -- Amplex-Limit Model -- Conceptual Exploration Through Structured Inquiry and Reframing (ConExSIR) -- 2.2.3 Reason 3: Externalization of Tsugoes Network for Considering Useful Data -- 2.3 Creativity -- 2.4 From Chance Discovery to Innovators´ Marketplace on Data Jackets (IMDJ) -- 2.5 The Roadmap for Interactive Innovation with the Market of Data -- 2.6 From the Past to the Present of Data Marketplace -- 2.6.1 Data Marketing Businesses: An Overview -- 2.6.2 Survey on Data Marketing Businesses -- 2.6.3 Data Market Business Trends in Countries/Regions -- Japan -- United States -- European Union (EU) -- China -- 2.6.4 Data Marketplaces in the Future -- 2.7 Summary -- References -- Chapter 3: Tools for Activating Data Marketplace (1) -- 3.1 Data Jackets for Representation of One´s Own Knowledge About Data -- 3.2 Method of Innovators´ Marketplace on Data Jackets -- 3.2.1 Innovators´ Marketplace as the Basis for IMDJ -- 3.2.2 The Procedure of IMDJ -- 3.3 The Formal Definition of DJs and Their Role in Satisfying Requirements -- 3.4 Analogy Applied on the Predicate-Logic Representations -- 3.5 Case Summaries of IMDJ.
3.6 Action Planning -- 3.6.1 Scenario Generation to Activate Actions -- 3.6.2 Outline of Action Planning -- 3.6.3 Action Planning Sheet -- 3.6.4 Action Planning Process with Example -- 3.7 Extension of IMDJ by Coupling with Living Lab -- 3.7.1 The Process of IMDJ with LL -- 3.8 Summary -- References -- Chapter 4: Tools for Activating Data Marketplace (2) -- 4.1 Data Jacket Store: Data Platform with Retrieval System -- 4.1.1 Why Is It Difficult to Discover Data Related to Our Interests? -- 4.1.2 Reuse of Knowledge for Data Utilization -- 4.1.3 Implementation -- 4.1.4 Performance -- 4.2 Variable Quest: Inferring Method of Variables -- 4.2.1 Design of Data -- 4.2.2 Data Similarity and Co-occurrence of Variables -- 4.2.3 Estimation Process of Variables -- 4.2.4 Implementation and Performance -- 4.3 TEEDA: A Platform for Call for Data and Matching -- 4.3.1 Call for Data and Matching -- 4.3.2 Data Requests and Providable Data -- 4.3.3 Implementation of TEEDA as a Web Application -- 4.3.4 Use Case and the Findings Using TEEDA -- 4.4 Web-Based IMDJ: Accelerating Communications for Innovation -- 4.4.1 Why Discuss Data Utilization on the Web? -- 4.4.2 Ordinal IMDJ Process -- 4.4.3 How to Use Web IMDJ -- 4.4.4 Face-to-Face Versus Online Discussions -- 4.4.5 Experiments and Discussion -- 4.5 Human Resource Finder -- 4.5.1 Stakeholders in Scenarios -- 4.5.2 Knowledge Structuring of Scenarios -- 4.5.3 Dataset Extension and Relationship Estimation -- 4.5.4 Implementation and Use Cases -- 4.6 Summary -- References -- Chapter 5: Knowledge Structuring and Acquisition for Data Exchange -- 5.1 Knowledge Representation for Data Utilization -- 5.1.1 Knowledge Structuring for Data Utilization -- 5.1.2 A Case of Open Data Exchange Platform: Yokohama and Kawasaki Cities -- 5.1.3 A Case of Discussion on COVID-19 Pandemic. 5.1.4 How to Use Structured Data-Related Knowledge in the Future -- 5.2 Datascape Analysis for Understanding the Data Exchange Ecosystem -- 5.2.1 Our Motivation and Datascape Analysis -- 5.2.2 Variable Characteristics: Frequency and Distribution -- 5.2.3 Data Network with Shared Variables -- 5.2.4 Data Combinability with Centrality Values -- 5.2.5 Suggestions for Data Platforms Regarding Data Economy Policies -- 5.3 Stakeholder-Centric Value Chain of Data Ecosystem -- 5.3.1 Understanding the Data Exchange Ecosystem from Business Players and Their Roles -- 5.3.2 Stakeholder-Centric Value Chain of Data -- 5.3.3 Structural Characteristics of the Data Exchange Ecosystem -- 5.3.4 Knowledge Structuring and Workshop-Styled Usage of SVC -- 5.4 Summary -- References -- Chapter 6: Case Studies of Innovators´ Marketplace on Data Jackets -- 6.1 The Triple as the Representation of Case Summaries in IMDJ -- 6.2 Streetlight Visualizer: Safety of Roads for Pedestrians -- 6.3 Improvement of Working Conditions -- 6.4 Machine Learning Applied to Physics via IMDJ -- 6.5 A New Problem of Data Science Externalized via Other IMDJ Sessions -- 6.6 Do Methods for Sequence Analysis Work for Change Explanation? -- 6.7 New Techniques for Change Explanation: Fruits of IMDJ -- 6.7.1 New Technique 1: Tangled String -- Applied Case of TS (1): Finding Triggers of Contextual Shifts in Discourse -- Applied Case of TS (2): Finding Noteworthy Body Movements -- Applied Case of TS (3): Features in the Changes in Markets -- 6.7.2 New Technique 2: Graph-Based Entropy -- 6.8 Analogy from One Success Case to Another: Toward the Explanation of Earthquake Precursors -- 6.9 Data Co-creation Project in Tokyo Marunouchi Area (2018-2019) -- 6.10 Cross-Media Trend and Promotion Measurement Framework -- 6.11 Data Jackets in the Data Society Alliance in Japan -- 6.12 Summary -- References. Chapter 7: Conclusions -- Index. |
| Record Nr. | UNINA-9910633928603321 |
Hayashi Teruaki
|
||
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||