Advances in Chance Discovery Extended Selection from International Workshops
Since year 2000, scientists on artificial and natural intelligences started to study chance discovery - methods for discovering events/situations that significantly affect decision making. Partially because the editors Ohsawa and Abe are teaching at schools of Engineering and of Literature with shar...
| Other Authors: | , |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2013, 2013
|
| Edition: | 1st ed. 2013 |
| Series: | Studies in Computational Intelligence
|
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 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