Browsing image collections with representations of common-sense activities
Journal of the American Society for Information Science and Technology
A maximum entropy approach to identifying sentence boundaries
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Automated story capture from conversational speech
Proceedings of the 3rd international conference on Knowledge capture
Say Anything: A Massively Collaborative Open Domain Story Writing Companion
ICIDS '08 Proceedings of the 1st Joint International Conference on Interactive Digital Storytelling: Interactive Storytelling
Engagement vs. Deceit: Virtual Humans with Human Autobiographies
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Say Anything: A Demonstration of Open Domain Interactive Digital Storytelling
ICIDS '09 Proceedings of the 2nd Joint International Conference on Interactive Digital Storytelling: Interactive Storytelling
A Semantic Triplet Based Story Classifier
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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Among the most interesting ways that people share knowledge is through the telling of stories, i.e. first-person narratives about real-life experiences. Millions of these stories appear in Internet weblogs, offering a potentially valuable resource for future knowledge management and training applications. In this paper we describe efforts to automatically capture stories from Internet weblogs by extracting them using statistical text classification techniques. We evaluate the precision and recall performance of competing approaches. We describe the large-scale application of story extraction technology to Internet weblogs, producing a corpus of stories with over a billion words.