Advances in Artificial Intelligence

Advances in Artificial Intelligence: 28th Canadian Conference on Artificial Intelligence, Canadian AI 2015, Halifax, Nova Scotia, Canada, June 2-5, … (Lecture Notes in Computer Science)

This book constitutes the refereed proceedings of the 28th Canadian Conference on Artificial Intelligence, Canadian AI 2015, held in Halifax, Nova Scotia, Canada, in June 2015.The 15 regular papers and 12 short papers presented together with 8 papers from the Graduate Student Symposium were carefully reviewed and selected from 81 submissions.  The papers are organized in topical sections such as agents, uncertainty and games; AI applications; NLP, text and social media mining; data mining and machine learning.

Table of Contents

Chapter 1. Exploiting Semantics in Bayesian Network Inference Using Lazy Propagation
Chapter 2. Darwinian Networks
Chapter 3. Improvements to the Linear Optimization Models of Patrol Scheduling for Mobile Targets
Chapter 4. Trajectory Generation with Player Modeling
Chapter 5. Policies, Conversations, and Conversation Composition
Chapter 6. Task Allocation in Robotic Swarms: Explicit Communication Based Approaches
Chapter 7. Budget-Driven Big Data Classification
Chapter 8. Inferring User Profiles in Online Social Networks Using a Partial Social Graph
Chapter 9. An Improved Machine Learning Approach for Selecting a Polyhedral Model Transformation
Chapter 10. Dynamic Budget-Constrained Pricing in the Cloud
Chapter 11. Visual Predictions of Traffic Conditions
Chapter 12. Privacy-Aware Wrappers
Chapter 13. Analyzing Productivity Shifts in Meetings
Chapter 14. Temporal Feature Selection for Noisy Speech Recognition
Chapter 15. Simulating Naming Latency Effects
Chapter 16. On Assessing the Sentiment of General Tweets
Chapter 17. Real-Time Sentiment-Based Anomaly Detection in Twitter Data Streams
Chapter 18. Sentiment and Factual Transitions in Online Medical Forums
Chapter 19. Abstractive Meeting Summarization as a Markov Decision Process
Chapter 20. Rule Extraction from Random Forest: The RF+HC Methods
Chapter 21. A Density-Penalized Distance Measure for Clustering
Chapter 22. Learning Paired-Associate Images with an Unsupervised Deep Learning Architecture
Chapter 23. Incremental Cluster Updating Using Gaussian Mixture Model
Chapter 24. Emotional Affect Estimation Using Video and EEG Data in Deep Neural Networks
Chapter 25. Active Learning with Clustering and Unsupervised Feature Learning
Chapter 26. STOCS: An Efficient Self-Tuning Multiclass Classification Approach
Chapter 27. Consolidation Using Sweep Task Rehearsal: Overcoming the Stability-Plasticity Problem
Chapter 28. Resolving Elections with Partial Preferences Using Imputation
Chapter 29. Novel Game Playing Strategies Using Adaptive Data Structures
Chapter 30. Auto-FAQ-Gen: Automatic Frequently Asked Questions Generation
Chapter 31. Representational Transfer in Deep Belief Networks
Chapter 32. Unsupervised Multi-modal Learning
Chapter 33. On the Usage of Discourse Relations Across Texts with Different Readability Levels
Chapter 34. A Framework for Discovering Bursty Events and Their Relationships from Online News Articles
Chapter 35. Behavioural Game Theory: Predictive Models and Mechanisms