Intelligence and Intelligent Systems (SIGODIS)

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Track Chairs

Vijayan Sugumaran, Oakland University, sugumara@oakland.edu
Rahul Singh, University of North Carolina – Greensboro, r_singh2@uncg.edu
Jai Ganesh, Mphasis NEXT Labs, jai.ganesh@mphasis.com
Donald Heath, University of Wisconsin Oshkosh, drheath2@gmail.com

track Description

The purpose of this track is to provide a forum for academics and practitioners to identify and explore the issues, opportunities, and solutions regarding intelligence related to business and systems including the social web, intelligent systems design, implementation, integration and deployment. An increasing number of artificial intelligence-based systems are being developed in different application domains employing a variety of tools and technologies. This track is intended to increase cross-fertilization of ideas from these areas, share lessons learned and stimulate areas for further research.

Mini-Track 1: Application of Intelligent Agent and Multi-Agent Systems

Vijayan Sugumaran, Oakland University, sugumara@oakland.edu
Stefan Kirn, Universität Hohenheim, stefan.kirn@uni-hohenheim.de

Multi-agent systems and semantic technologies have been recognized as one of the most important Information Technologies and have received considerable attention from both academia and industry. Significant progress has been made over the last few years in the development of multi-agent systems and semantic web applications in a variety of fields such as electronic commerce, supply chain management, resource allocation, intelligent manufacturing, mass customization, information retrieval and filtering, decision support, simulation, and healthcare. While research on various aspects of multi-agent systems and semantic technologies is progressing at a very fast pace, this is only the beginning. There are still a number of issues that have to be explored in terms of the design, implementation and deployment semantic web applications and multi-agent systems. For example, formal approaches for agent-oriented modeling, ontology based information system, ontology engineering, semantic web for e-learning, and organizational impact of agent-based systems & semantic technologies are some of the areas in need of further research.

Mini-Track 2: Web and Social Intelligence

Jai Ganesh, Mphasis NEXT Labs, jai.ganesh@mphasis.com

Social Media refers to the adoption of open technologies and architectural frameworks to facilitate participative computing. Social Media is about harnessing the potential of the Internet in a more collaborative and peer-to-peer manner with emphasis on social interaction. It has less to do with technology and more to do with a metamorphosis aimed at facilitating collaborative participation and leveraging the collective intelligence of peers. The aim of this mini-track is to welcome papers that investigate intelligent systems in a web/social context.

Mini-Track 3: Customer Experience and Organizational Intelligence

Donald Heath, University of Wisconsin Oshkosh, drheath2@gmail.com
Rahul Singh, University of North Carolina – Greensboro, r_singh2@uncg.edu

Increasingly, organizations are interacting with current and potential customers across a plenitude of IT-mediated “touch points”. Consequently, coordinating strategies will likely dominate management thought in the near and intermediate term as the number and variety of these “touch points” continues to expand. Effective strategies will rely on quality practitioner and academic research on a variety of issues, such as how to: differentiate user experience across points of interaction, increase reach to the consumer, improve conversion rates, sustain consumer loyalty, manage the global and the local experience, etc. The end customer is at the focus, with various technologies, devices and networks facilitating seamless computing, communication, collaboration as well as commerce related functionalities to the end users. This is made possible by embedding data, sensors, controllers, and other devices into the physical and virtual spaces of human beings thereby facilitating seamless interactions and co-engagement between the end customer and the organization. We invite research which addresses or expands on these ideas.

Mini-Track 4: Semantic Technologies and Big Data Analytics

Victoria Y. Yoon, Virginia Commonwealth University, vyyoon@vcu.edu

The vision of Semantic Integration for Big Data Analytics is to have heterogeneous data linked in such a way that machines can understand its meanings for the exchange and reuse of large amounts of data across heterogeneous data sources. The semantic representation of heterogeneous data, augmented with ontology of domain theories, will enable us to link a large network of human knowledge and make this knowledge machine-understandable. This will in turn enable various knowledge systems to effectively analyze and reason the big data to uncover useful information. Semantic integration has made significant progress over several years, however, the current state of semantic integration requires significant improvements to make it more effective in a broader range of applications. This mini-track seeks papers that address the issues related to designing, developing, and evaluating the semantic integration of large volume of heterogeneous data from the technical, behavioral, economical, or managerial perspectives.

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