WordNet: a lexical database for English
Communications of the ACM
Interactive storytelling environments: coping with cardiac illness at Boston's Children's Hospital
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Bringing drama into a virtual stage
Proceedings of the third international conference on Collaborative virtual environments
Foundations of genetic programming
Foundations of genetic programming
Knowledge-based extraction of named entities
Proceedings of the eleventh international conference on Information and knowledge management
Domain-Specific Web Search with Keyword Spices
IEEE Transactions on Knowledge and Data Engineering
The CPR Model for Summarizing Video
Multimedia Tools and Applications
CARA: A Cultural-Reasoning Architecture
IEEE Intelligent Systems
ACM Transactions on Computational Logic (TOCL)
A multimedia recommender integrating object features and user behavior
Multimedia Tools and Applications
Photos, time, navigation, visualization, recommendation and interactive TV: issues and contributions
Multimedia Tools and Applications
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There are numerous applications where there is a need to rapidly infer a story about a given subject from a given set of potentially heterogeneous data sources. In this paper, we formally define a story to be a set of facts about a given subject that satisfies a "story length" constraint. An optimal story is a story that maximizes the value of an objective function measuring the goodness of a story. We present algorithms to extract stories from text and other data sources. We also develop an algorithm to compute an optimal story, as well as three heuristic algorithms to rapidly compute a suboptimal story. We run experiments to show that constructing stories can be efficiently performed and that the stories constructed by these heuristic algorithms are high quality stories. We have built a prototype STORY system based on our model--we briefly describe the prototype as well as one application in this paper.