Paper Info
Title
Text Mining Emergent Human Behaviors for Interactive Systems
Abstract
People engage with thousands of situations, activities, and objects on a daily basis. Hand-coding this knowledge into interactive systems is prohibitively labor-intensive, but fiction captures a vast number of human lives in moment to moment detail. In this paper, we bootstrap a knowledge graph of human activities by text mining a large dataset of modern fiction on the web. Our knowledge graph, Augur, describes human actions over time as conditioned by nearby locations, people, and objects. Applications can use this graph to react to human behavior in a data-driven way. We demonstrate an Augur-enhanced video game world in which non-player characters follow realistic patterns of behavior, interact with their environment and each other, and respond to the user's behavior.
Year
DOI
Venue
2015
10.1145/2702613.2732805
CHI Extended Abstracts
Keywords
Field
DocType
user interfaces,crowdsourcing,information extraction,data mining,fiction
Graph,World Wide Web,Text mining,Knowledge graph,Crowdsourcing,Computer science,Human–computer interaction,Information extraction,Human behavior
Conference
Citations 
PageRank 
References 
0
0.34
8
Authors
3
Name
Order
Citations
PageRank
Ethan Fast11408.45
Pranav Rajpurkar255524.99
Michael S. Bernstein38604393.80