Interactive Relevance Search and Modeling: Support for Expert-Driven Analysis of Multimodal Data (bibtex)
by Miller, Chreston, Quek, Francis and Morency, Louis-Philippe
Abstract:
In this paper we present the findings of three longitudinal case studies in which a new method for conducting multimodal analysis of human behavior is tested. The focus of this new method is to engage a researcher integrally in the analysis process and allow them to guide the identification and discovery of relevant behavior instances within multimodal data. The case studies resulted in the creation of two analysis strategies: Single-Focus Hypothesis Testing and Multi-Focus Hypothesis Testing. Each were shown to be beneficial to multimodal analysis through supporting either a single focused deep analysis or analysis across multiple angles in unison. These strategies exemplified how challenging questions can be answered for multimodal datasets. The new method is described and the case studies’ findings are presented detailing how the new method supports multimodal analysis and opens the door for a new breed of analysis methods. Two of the three case studies resulted in publishable results for the respective participants.
Reference:
Interactive Relevance Search and Modeling: Support for Expert-Driven Analysis of Multimodal Data (Miller, Chreston, Quek, Francis and Morency, Louis-Philippe), In Proceedings of the 15th ACM on International conference on multimodal interaction, ACM, 2013.
Bibtex Entry:
@inproceedings{miller_interactive_2013,
	address = {Sydney, Australia},
	title = {Interactive {Relevance} {Search} and {Modeling}: {Support} for {Expert}-{Driven} {Analysis} of {Multimodal} {Data}},
	shorttitle = {Interactive relevance search and modeling},
	url = {http://ict.usc.edu/pubs/Interactive%20relevance%20search%20and%20modeling%20-%20Support%20for%20expert-driven%20analysis%20of%20multimodal%20data.pdf},
	abstract = {In this paper we present the findings of three longitudinal case studies in which a new method for conducting multimodal analysis of human behavior is tested. The focus of this new method is to engage a researcher integrally in the analysis process and allow them to guide the identification and discovery of relevant behavior instances within multimodal data. The case studies resulted in the creation of two analysis strategies: Single-Focus Hypothesis Testing and Multi-Focus Hypothesis Testing. Each were shown to be beneficial to multimodal analysis through supporting either a single focused deep analysis or analysis across multiple angles in unison. These strategies exemplified how challenging questions can be answered for multimodal datasets. The new method is described and the case studies’ findings are presented detailing how the new method supports multimodal analysis and opens the door for a new breed of analysis methods. Two of the three case studies resulted in publishable results for the respective participants.},
	booktitle = {Proceedings of the 15th {ACM} on {International} conference on multimodal interaction},
	publisher = {ACM},
	author = {Miller, Chreston and Quek, Francis and Morency, Louis-Philippe},
	month = dec,
	year = {2013},
	keywords = {Virtual Humans, UARC},
	pages = {149--156}
}
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