第一届国际情感计算与情感认知研讨会 1st Int. Workshop on Affective Computing and Emotion Recognition ACER 2017

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活动简介

Affective computing became a key scenario for Artificial Intelligence. Various emotion-mining techniques can be exploited for creating and automating personalized interfaces or subcomponent technology for larger systems, i.e. in business intelligence, affective tutoring, recommender systems, social robots.

Different from sentiment analysis, this approach works at a deeper level of abstraction, aiming to recognize specific emotions and not only the positive/negative sentiment, to extract, manage and predict emotions in limited sets, basing on well-accepted or novel models, thus to use them to be reported/classified or understood/elicited/expressed by a machine.

The aim of the ACER workshop is to explore the Emotion Recognition area in depth, and to present, discuss and ideate novel affective computing and emotion recognition techniques in WI-related task, providing a cross-fertilized network of different communities focused on research, development and applications of emotion recognition.

ACER invites original high-quality papers: conceptual, empirical as well as theoretical papers are welcome; graduate students are invited to submit their WI thesis showcase; experienced researchers are warmly invited to submit novel or updated versions of their work.

征稿信息

重要日期

2017-05-21

初稿截稿日期

2017-06-18

初稿录用日期

2017-06-26

终稿截稿日期

征稿范围

Topics include but are not limited to:

Affective computing and Emotion Recognition in Web Intelligence
Models of emotions, measuring emotions on the Web
Multidimensional emotion recognition
Emotional/affective process mining
Emotions in the crowds, emotions and sentiments in social networks, link prediction
Affective tagging and emotion recognition in Recommender Systems
Emotion recognition across cultural variations, local-culture emotion recognition
Semantic Emotion Recognition, Linked Data in affective spaces, affective ontologies, and sentic computing
Natural Language Processing, Emotion extraction from text
Automated emotion/mood tagging with emoji/memes
Facial/gestures/visual emotion recognition and synthesis, emotion recognition in video streaming
Emotional, affective states associated with music, audio or speech
Recognition of emotions elicited by artistic stimuli e.g. paintings
Affective computing, emotion recognition from Brain Interfaces or sensors e.g. EMG sensors, motion sensors, GPS tracking
Biomimetic modeling of emotions, models of emotionally communicative behavior, evolved or emergent emotional behavior
Emotion recognition in social robots, intelligent interfaces, symbiotic cognitive systems
Affective states or emotions expressed by web-based/cloud robots, web-based Artificial intelligence, affective human-computer interfaces
Online Human-Bot emotional interactions, real-time integrated systems
Novel technologies using emotional elements that can better engage disabled people, e.g. with ASC (Autism Spectrum Conditions), in learning and communication
Assertive robots, assertive artificial intelligence, artificial empathy and emotional intelligence in human-robot interactions
Emotion recognition in business/government intelligence and marketing strategies
Applications using web-based machine learning services e.g. IBM Watson, Google TensorFlow
Specialized interfaces and animation technologies, applications in games and education, e.g. affective tutoring
Ethical challenges on affective computing and emotion recognition in Web Intelligence, e.g. deception in emotions-aware HRI, emotional privacy, side effects and evolution of humanity using affective-intelligent web services
Applicable lessons from other fields (e.g. robotics, AI, psychology)