Temporal reasoning based on semi-intervals
Artificial Intelligence
Class-based n-gram models of natural language
Computational Linguistics
Maintaining knowledge about temporal intervals
Communications of the ACM
Temporal Constraints: A Survey
Constraints
Soft Computing and Fuzzy Logic
IEEE Software
Unsupervised Learning with Mixed Numeric and Nominal Data
IEEE Transactions on Knowledge and Data Engineering
Discovering Temporal Patterns for Interval-Based Events
DaWaK 2000 Proceedings of the Second International Conference on Data Warehousing and Knowledge Discovery
Model modification in structural equation modeling by imposing constraints
Computational Statistics & Data Analysis
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
MacVisSTA: a system for multimodal analysis
Proceedings of the 6th international conference on Multimodal interfaces
Algorithms for time series knowledge mining
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Recognizing gaze aversion gestures in embodied conversational discourse
Proceedings of the 8th international conference on Multimodal interfaces
Unsupervised pattern mining from symbolic temporal data
ACM SIGKDD Explorations Newsletter - Special issue on data mining for health informatics
Interaction techniques for the analysis of complex data on high-resolution displays
ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
Fun to develop embodied skill: how games help the blind to understand pointing
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
Structuring ordered nominal data for event sequence discovery
Proceedings of the international conference on Multimedia
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Conversation scene analysis based on dynamic Bayesian network and image-based gaze detection
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
VACE multimodal meeting corpus
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
ICCHP'06 Proceedings of the 10th international conference on Computers Helping People with Special Needs
A multimodal analysis of floor control in meetings
MLMI'06 Proceedings of the Third international conference on Machine Learning for Multimodal Interaction
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Structural and temporal inference search (STIS): pattern identification in multimodal data
Proceedings of the 14th ACM international conference on Multimodal interaction
Interactive data-driven discovery of temporal behavior models from events in media streams
Proceedings of the 20th ACM international conference on Multimedia
Interactive relevance search and modeling: support for expert-driven analysis of multimodal data
Proceedings of the 15th ACM on International conference on multimodal interaction
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Multimodal analysis of human behavior is ultimately situated. The situated context of an instance of a behavior phenomenon informs its analysis. Starting with some initial (user-supplied) descriptive model of a phenomenon, accessing and studying instances in the data that are matches or near matches to the model is essential to refine the model to account for variations in the phenomenon. This inquiry requires viewing the instances within-context to judge their relevance. In this paper, we propose an automatic processing approach that supports this need for situated analysis in multimodal data. We process events on a semi-interval level to provide detailed temporal ordering of events with respect to instances of a phenomenon. We demonstrate the results of our approach and how it facilitates and allows for situated multimodal analysis.