
Intelligent Information and Database Systems
Description
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The 161 revised papers presented were carefully reviewed and selected from more than 472 submissions. The papers included cover the following topics: intelligent database systems, data warehouses and data mining, natural language processing and computational linguistics, semantic Web, social networks and recommendation systems, collaborative systems and applications, e-bussiness and e-commerce systems, e-learning systems, information modeling and requirements engineering, information retrieval systems, intelligent agents and multi-agent systems, intelligent information systems, intelligent internet systems, intelligent optimization techniques, object-relational DBMS, ontologies and knowledge sharing, semi-structured and XML database systems, unified modeling language and unified processes, Web services and semantic Web, computer networks and communication systems.
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Content
- Intro
- Introduction
- Knowledge Integration Task
- Task Definition
- Integration Task Common-Sense Requirements
- Integration Strategy
- Reflection of Agent's Cognitive State
- Integration Procedure
- Integration Properties
- Computational Example
- Conclusions
- Introduction
- eHealth Systems: State of the Art
- Architecture of the eHealth Systems
- Proposed Architecture: Benefits Achieved
- System Analysis in Healthcare and Wellness: Case Study
- Summary
- Introduction
- Related Works
- Methodologies
- Local Neighbor Enrichment Phase
- Matching Phase
- Experiments
- Data Sets
- Evaluation Method
- Evaluation Result
- Conclusions
- Introduction
- Background and Related Work
- Charging Scheduler Design
- System Model
- Task Model
- Initial Population Selection
- Genetic Operations
- Performance Measurement
- Conclusions
- Introduction
- The Domain
- Notations
- The Penalty Avoiding Rational Policy Making Algorithm
- Improved PARP
- Keepaway Task
- Basic Setting
- State Variables
- Actions
- The Soccer Robot System
- Soccer Robot
- Host System
- Position and Orientation
- Real World Experimentation
- Setting
- Reward and Penalty
- Results
- Discussion
- Conclusion
- Introduction
- DRFLogitBoost: A Double Randomized Decision Forest Incorporated with LogitBoosted Decision Stumps
- Real LogitBoosting (Real LogitBoost)
- Problem Setup and Discussion of the Experimental Results
- Problem 1: Credit Score Classification
- Problem 2: Short Term Extreme Rainfall Forecast Problem
- Conclusion
- Introduction
- Related Work
- Structured Output Learning Using AdaBoostSeq Algorithm
- Ordering Heuristics for AdaBoostSeq Algorithm
- Experiments and Results
- Conclusions
- Preliminaries
- Testing Rational -Codes
- A Language Algorithm
- An Algorithm Basing on Monoids
- A Graph Algorithm
- A Quadratic Algorithm for Testing of -Codes
- Introduction
- Problem Statement
- Functional Magnetic Resonance Imaging (fMRI)
- Related Works
- Dataset and Data Collection Procedure
- Procedure
- Our Approach
- Dimensionality Reduction/Feature Selection
- Classification
- Experimental Results
- Comparison between Mitchell et al.'s Approach vs. Our Approach
- Effect of Number of Active Voxels on Accuracy of the Classifier
- Cross-subjects Classification Results
- Conclusion
- Introduction
- Background
- Discriminative Motif Discovery
- DMOPS Motif Finding
- Semi-Supervised Discriminative Motif Finding
- Our Framework
- DMOPS Motif Finding Algorithm
- Motif Matching and Label Assigning Algorithm
- Application to Study NS5A Region of HepatitisC Virus and Resistance to IFN/RBV Therapy
- Data
- Experiment
- Conclusion
- Introduction
- Decision Problem Statement
- The Recognition Algorithm
- Zero-One Loss Function
- Node-Dependent Fuzzy Loss Function
- Cost Model
- Cost for Two-Stage Binary Classifier
- Illustrative Example
- Conclusion
- Introduction
- Method
- Neighborhood Selection
- K-nn Modification
- Eigenvalues from LLE and Isomap
- Experiment
- Datasets
- Parameters
- Result
- Conclusion
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