3 results match your criteria Applied Artificial Intelligence[Journal]

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Automatic Identification of Character Types from Film Dialogs.

Appl Artif Intell 2016 Nov;30(10):942-973

Austrian Research Institute for Artificial Intelligence OFAI, Vienna, Austria.

We study the detection of character types from fictional dialog texts such as screenplays. As approaches based on the analysis of utterances' linguistic properties are not sufficient to identify all fictional character types, we develop an integrative approach that complements linguistic analysis with interactive and communication characteristics, and show that it can improve the identification performance. The interactive characteristics of fictional characters are captured by the descriptive analysis of semantic graphs weighted by linguistic markers of expressivity and social role. Read More

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http://dx.doi.org/10.1080/08839514.2017.1289311DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5652896PMC
November 2016
2 Reads

Robust Feature Selection Technique using Rank Aggregation.

Appl Artif Intell 2014 Jan;28(3):243-257

College of Science and Engineering University of Minnesota at Twin Cities.

Although feature selection is a well-developed research area, there is an ongoing need to develop methods to make classifiers more efficient. One important challenge is the lack of a universal feature selection technique which produces similar outcomes with all types of classifiers. This is because all feature selection techniques have individual statistical biases while classifiers exploit different statistical properties of data for evaluation. Read More

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http://dx.doi.org/10.1080/08839514.2014.883903DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4019401PMC
January 2014
9 Reads

Maintaining Engagement in Long-term Interventions with Relational Agents.

Appl Artif Intell 2010 Jul;24(6):648-666

Northeastern University College of Computer and Information Science, 360 Huntington Ave, WVH202, Boston, MA 02115.

We discuss issues in designing virtual humans for applications which require long-term voluntary use, and the problem of maintaining engagement with users over time. Concepts and theories related to engagement from a variety of disciplines are reviewed. We describe a platform for conducting studies into long-term interactions between humans and virtual agents, and present the results of two longitudinal randomized controlled experiments in which the effect of manipulations of agent behavior on user engagement was assessed. Read More

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http://dx.doi.org/10.1080/08839514.2010.492259DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3035950PMC
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