Tree-Based Mining for Discovering Patterns of Human Interaction in Meetings

Authors:
Zhiwen Yu;Zhiyong Yu;Xingshe Zhou;Christian Becker;Yuichi Nakamura
Affiliations:
Northwestern Polytechnical University, Xi An;Fuzhou University, Fuzhou;Northwestern Polytechnical University, Xi An;Mannheim University, Mannheim;Kyoto University, Kyoto
Venue:
IEEE Transactions on Knowledge and Data Engineering
Year:
2012

Citing 0
Cited 3

Viewing by interactions: media-oriented operators for reviewing recorded sessions on tv

Proceddings of the 9th international interactive conference on Interactive television
Browsing interaction events in recordings of small group activities via multimedia operators

Proceedings of the 18th Brazilian symposium on Multimedia and the web
Understanding social relationship evolution by using real-world sensing data

World Wide Web

Quantified Score

Hi-index	0.00

Visualization

Abstract

Discovering semantic knowledge is significant for understanding and interpreting how people interact in a meeting discussion. In this paper, we propose a mining method to extract frequent patterns of human interaction based on the captured content of face-to-face meetings. Human interactions, such as proposing an idea, giving comments, and expressing a positive opinion, indicate user intention toward a topic or role in a discussion. Human interaction flow in a discussion session is represented as a tree. Tree-based interaction mining algorithms are designed to analyze the structures of the trees and to extract interaction flow patterns. The experimental results show that we can successfully extract several interesting patterns that are useful for the interpretation of human behavior in meeting discussions, such as determining frequent interactions, typical interaction flows, and relationships between different types of interactions.