-------- Forwarded Message -------- Subject: [AISWorld] CFP for Secon d International Workshop on Multimedia Pragmatics (MMPrag'19) Date: Wed, 16 Jan 2019 13:49:39 -0500 From: William Grosky wgrosky@umich.edu To: aisworld@lists.aisnet.org
CALL FOR PAPERS
SECOND INTERNATIONAL WORKSHOP ON MULTIMEDIA PRAGMATICS (MMPrag'19) March 30, 2019 - San Jose, California Co-Located with the IEEE SECOND INTERNATIONAL CONFERENCE ON MULTIMEDIA INFORMATION PROCESSING AND RETRIEVAL (MIPR'19) March 28-30, 2019 - San Jose, California
Venue: Crowne Plaza San Jose-Silicon Valley Hotel, 777 Bellew Drive, Milpitas, California 95053, +1 (408) 321-9500
Submission Website: https://easychair.org/conferences/?conf=mmprag19 Call for Papers: https://easychair.org/cfp/MMPrag19 Workshop Website: http://mipr.sigappfr.org/19/
====================================IMPORTANT DATES====================================================================
January 25, 2019 - Submissions due February 1, 2019 - Acceptance notification February 8, 2019 - Camera-ready papers and author registrations due March 30, 2019 - Workshop date ====================================DESCRIPTION========================================================================= Most multimedia objects are spatio-temporal simulacrums of the real world. This supports our view that the next grand challenge for our community will be understanding and formally modeling the flow of life around us, over many modalities and scales. As technology advances, the nature of these simulacrums will evolve as well, becoming more detailed and revealing more information concerning the nature of reality to us.
Currently, IoT is the state-of-the-art organizational approach to construct complex representations of the flow of life around us. Various, perhaps pervasive, sensors, working collectively, will broadcast to us representations of real events in real-time. It will be our task to continuously extract the semantics of these representations and possibly react to them by injecting some response actions into the mix to ensure some desired outcome.
In linguistics, pragmatics studies context and how it affects semantics. Context is usually culturally, socially, and historically based. For example, pragmatics would encompass a speaker’s intent, body language, and penchant for sarcasm, as well as other signs, often culturally based, such as the speaker’s type of clothing, which could influence a statement’s meaning. Generic signal/sensor- based retrieval should also use syntactical, semantic, and pragmatics-based approaches. If we are to understand and model the flow of life around us, this will be a necessity.
Our community has successfully developed various approaches to decode the syntax and semantics of these artifacts. The development of techniques that use contextual information is in its infancy, however. With the expansion of the data horizon, through the ever-increasing use of metadata, we can certainly leverage the semantic representation of all media to a more robust level.
The NLP community has its own set of approaches in semantics and pragmatics. Natural language is certainly an excellent exemplar of multimedia, and the use of audio and text features has played a part in the development of our field.
After a successful first workshop in Miami, we intend to continue this tradition with the second workshop.
====================================KEYNOTES============================================================================ Keynote 1 -- Adam Pease, Principal Scientist, Infosys Foothill Research, Palo Alto, California, USA
*Title: Conceptual Pragmatics: A Library of Logical Definitions
*Abstract: What is an apple, a jump or the number 2 and how can we hope to have a computer understand these things with any of the same depth or richness that people do? We now have machine learning systems that can mimic, at some level, human sensory subsystems, recognizing objects in pictures, or voices and words in streams of audio. But we also need a cognitive-level representation - one that not only can recognize patterns but also hold information about those patterns that allows for explanation and communication. A person can describe a previously unseen object to another person, who can then recognize it and understand its characteristics before seeing it, and before seeing it a million times. Someone who has never seen a child skip can still be told how to recognize skipping. We can tell another person the context of skipping, as an isolated action or the likely context in which such actions occur.
In this talk I describe a unified corpus of logically-expressed and computable meaning about concepts that has application in language and image understanding. It is a library of pragmatics that can be used to express facts independently of whether they are learned over many presentations of visual or auditory data, or related in communication. I also describe its application in image recognition and language understanding.
*Biography: Adam Pease is a Principal Scientist at the Infosys Foothill Research Center in Palo Alto. He has led research in ontology, linguistics, and formal inference, including development of the Suggested Upper Merged Ontology (SUMO), the Controlled English to Logic Translation (CELT) system, and the Sigma knowledge engineering environment. Sharing research under open licenses, in order to achieve the widest possible dissemination and technology transfer, has been a core element of his research program. He is the author of the book “Ontology: A Practical Guide”. ------------------------------------ Keynote 2 -- Amit Sheth -- Professor and Executive Director of Kno.e.sis, Wright State University, Dayton, Ohio, USA
*Title: On Exploiting Multimodal Information for Machine Intelligence and Natural Interactions - With Examples from Health Chatbots
*Abstract: The Holy Grail of machine intelligence is the ability to mimic the human brain. In computing, we have created silos in dealing with each modality (text/language processing, speech processing,image processing, video processing, etc.). However, the human brain’s cognitive and perceptual capability to seamlessly consume (listen and see) and communicate (writing/typing, voice, gesture) multimodal (text, image, video, etc.) information challenges the machine intelligence research. Emerging chatbots for demanding health applications present the requirements for these capabilities. To support the corresponding data analysis and reasoning needs, we have to explore a pedagogical framework consisting of semantic computing, cognitive computing, and perceptual computing (http://bit.ly/w-SCP). In particular, we have been motivated by the brain’s amazing perceptive power that abstracts massive amounts of multimodal data by filtering and processing them into a few concepts (representable by a few bits) to act upon. From the information processing perspective, this requires moving from syntactic and semantic big data processing to actionable information that can be weaved naturally into human activities and experience (http://bit.ly/w-CHE).
Exploration of the above research agenda, including powerful use cases, is afforded in a growing number of emerging technologies and their applications - such as chatbots and robotics. In this talk, I will provide these examples and share the early progress we have made towards building health chatbots (http://bit.ly/H-Chatbot) that consume contextually relevant multimodal data and support different forms/modalities of interactions to achieve various alternatives for digital health ( http://bit.ly/k-APH). I will also discuss the indispensable role of domain knowledge and personalization using domain and personalized knowledge graphs as part of various reasoning and learning techniques.
*Biography: Amit Sheth is an educator, researcher, and entrepreneur. He is the LexisNexis Ohio Eminent Scholar, and IEEE Fellow, an AAAI Fellow, and the executive director of Kno.e.sis - the Ohio Center of Excellence in Knowledge-enabled Computing. Kno.e.sis. is a multi- disciplinary Ohio Center of Excellence in BioHealth Innovation. Its faculty and researchers are computer scientists, cognitive scientists, biomedical researchers, and clinicians. Sheth is working towards a vision of Computing for Human Experience enabled by the capabilities at the intersection of AI (semantic, cognitive, and perceptual computing), Big and Smart Data (exploiting multimodal Physical-Cyber-Social data), and Augmented Personalized Health. His recent work has involved Web 3.0 technologies and involves enterprise, social sensor/IoT data and applications.
====================================AREAS===============================================================================
Authors are invited to submit regular papers (6 pages), short papers (4 pages), demo papers (4 pages), and extended abstracts (1 page max for a 5-minute presentation) at https://easychair.org/conferences/?conf=mmprag19.
Cross-cultural contributions are encouraged. Topics of interest include, but are not limited to:
- Affective computing - Annotation techniques for natural language/images/videos/other sensor-based modalities - Applications to ecology, environmental science, health sciences, social sciences - Computational semiotics - Deception detection - Digital humanities - Distributional semantics - Education and Tutoring Systems - Event modeling, recognition, and understanding - Gesture modeling, recognition, and understanding - Human-machine interaction - Integration of multimodal features - Machine learning for multimodal interaction - Multimodal analysis of human behavior - Multimodal data modeling, dataset development, sensor fusion - Ontologies - Semantic-based modeling and retrieval - Storytelling - Structured semantic embeddings - Word, sentence, and feature embeddings - generation, semantic property discovery, corpus dependencies, sensitivity analysis, retrieval aids
To be included in the IEEE Xplore Library, accepted papers must be registered and presented.
====================================ORGANIZATION========================================================================
Chairs: R. Chbeir, University of Pau, FR (richard.chbeir@univ-pau.fr) W. Grosky, University of Michigan-Dearborn, US (wgrosky@umich.edu)
Program Committee: Wael Abd-Almageed, ISI, USA Mohamed Abouelenien, University of Michigan-Dearborn, USA Rajeev Agrawal, ITL, ERDC, USA Akiko Aizawa, National Institute of Informatics, Japan Yiannis Aloimonos, University of Maryland, USA Anya Belz, University of Brighton, UK Renaldo Bonacin, CTI, BrazilSecondSec Fabricio Olivetti de Franca, Federal University of ABC, Brazil Julia Hirschberg, Columbia University, USA David Hogg, University of Leeds, UK Ashutosh Jadhav, IBM, USA Clement Leung, Hong Kong Baptist University, China Debanjan Mahata, Bloomberg, USA David Martins, Federal University of ABC, Brazil Adam Pease, Articulate Software, USA James Pustejovsky, Brandeis University, USA Terry Ruas, University of Michigan-Dearborn, USA Victoria Rubin, University of Western Ontario, Canada Shin'ichi Satoh, National Institute of Informatics, Japan Amit Sheth, Wright State University, USA Peter Stanchev, Kettering University, USA Joe Tekli, American University of Lebanon, Lebanon