Paper: Learning From Collective Human Behavior to Introduce Diversity in Lexical Choice

ACL ID P11-1110
Title Learning From Collective Human Behavior to Introduce Diversity in Lexical Choice
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

We analyze collective discourse, a collective human behavior in content generation, and show that it exhibits diversity, a property of general collective systems. Using extensive analysis, we propose a novel paradigm for de- signing summary generation systems that re- flect the diversity of perspectives seen in real- life collective summarization. We analyze 50 sets of summaries written by human about the same story or artifact and investigate the diver- sity of perspectives across these summaries. We show how different summaries use vari- ous phrasal information units (i.e., nuggets) to express the same atomic semantic units, called factoids. Finally, we present a ranker that em- ploys distributional similarities to build a net- work of words, and captures the diversity of perspectives by...