Intelligence and Intelligent Systems (SIGODIS)


Track Chairs:

Vijayan Sugumaran, Oakland University,  This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Rahul Singh, University of North Carolina – Greensboro,  This e-mail address is being protected from spambots. You need JavaScript enabled to view it

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.

This Track is sponsored by AIS Special Interest Group on Ontology Driven Intelligent Systems (SIGODIS). Selected papers from this Track will be invited for fast tracked publication in special issues of the International Journal of Intelligent Information Technologies (IJIIT) and the Journal of Information Science and Technology (JIST).

Minitracks:

Application of Intelligent Agent and Multi-Agent Systems

Vijayan Sugumaran, Oakland University, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Stefan Kirn, Universität Hohenheim, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

While research on various aspects of multi-agent systems and semantic technologies is progressing at a fast pace, there are still a number of issues that have to be explored in terms of the design and implementation of agent based systems. The purpose of this mini-track is to provide a forum for academics and practitioners to identify and explore the issues and opportunities in using agent technologies for the design, implementation, and deployment of intelligent systems. This mini-track is intended to increase cross-fertilization of ideas from various domains, and share the lessons learned. It is expected to serve as the spring-board for gathering and disseminating experiences gained in implementing and integrating agent based systems. Best papers from this mini-track will be fast tracked for publication in a special issue of International Journal of Intelligent Information Technologies (IJIIT).

Business Issues in Web and Social Intelligence

Jai Ganesh, Infosys, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Donald R Heath, University of North Carolina at Greensboro, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Rahul Singh, University of North Carolina at Greensboro, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

Social Media facilitates participative computing and harnesses the Internet in a more collaborative and peer-to-peer manner with an 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.

Enterprises explore Social Media Strategies to engage their end customers and build competitive differentiation. Content generated in social networking environments include discussion threads, chat room conversations, blogs, and any other content posted by users. The accumulated content and ideas becomes an aggregation of the collective intelligence of the user community participating in those sites. The accumulated content can be an asset that has value for both owners of the sites as well as the organizations whose products and services are being discussed. Multiple inference options exist for understanding the behavior of online social networks. One area of analysis is that of focusing on the content purely, to try to discover concepts, facts or opinions from the content posted by users. A second type of analysis is to focus on the users themselves to discover networks (or sub-groups) in the community and to learn how those sub-groups get formed or change.

Customer Experience and Organizational Intelligence

Jai Ganesh, Infosys, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Don Heath, University of North Carolina at Greensboro, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Rahul Singh, University of North Carolina at Greensboro, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

Enterprises are increasingly adopting technologies which offer immersive experiences for their end customers. This is driven by increasing competitive pressures, the need to differentiate, expand reach to the consumer, improve conversion, and sustain customer loyalty. With online interactions poised for strong growth and likely to grow into a significant chunk of total business, enterprises are seeking answers to issues such as differentiating user experience on their points of interaction, increasing reach to the consumer, improving conversion rates on the website, sustaining consumer loyalty, 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 sensors, controllers, devices and data into the physical spaces of human beings thereby facilitating seamless interactions. Computing is revolutionizing the way humans interact with other humans, devices, applications, networks, sensors, infrastructure, machines, services etc. This provides interesting challenges for business intelligence and decision support. Such scenarios have characteristics such as pervasive computing devices including mobile phones, appliances, sensors etc., pervasive networks including wired and wireless networks, pervasive ecosystem entities participating from formal as well as informal social networks whereby entities engage across multiple locations, platforms etc., pervasive data resulting from exponential growth of  data (both structured as well as unstructured), ecosystem entities, sensors etc., pervasive computing and storage power available on the go via cloud computing technologies.

Modelling for Agents and Services

Ghassan Beydoun, University of Wollongong, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Rubén Fuentes, Universidad Complutense de Madrid, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Dongming Xu, University of Queensland, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

Recent modeling efforts in the agent software engineering community have produced many languages, methods and frameworks that facilitate the development of multiagent systems. There have also been many efforts to facilitate the use of agents to implement service-based systems and orthogonal efforts to model service-based systems. This mini-track seeks to encourage the exploration of the use of agent models to facilitate the modeling and delivery of service-based systems, using agent systems or otherwise. The purpose of this mini-track is to provide a forum for academics and practitioners to identify and explore the issues, opportunities, and solutions that improve the modeling of service systems and at the same time to further the scope of agent oriented software engineering.

Semantic Web and Ontology

Victoria Y Yoon, Virginia Commonwealth University, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Richard T Redmond, Virginia Commonwealth University, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

The vision of Semantic Web is to have data on the Web defined and linked in such a way that machines can understand its meanings for automation, and integration and reuse of data across various websites. The semantic representation of data, augmented with ontology of domain theories, will enable the Web to link a large network of human knowledge and make this knowledge machine-understandable. This will enable various knowledge systems to effectively process and reason the data to perform complex tasks. Semantic Web has been recognized as one of the most important Information Technologies and has received considerable attention from both academia and industry. Semantic Web has made significant progress over several years when numerous issues have been addressed and many applications have been developed. However, despite all of these advances, the current state of Semantic Web requires significant improvements to make it more effective in a broader range of applications.

This mini-track aims to bring academicians and practitioners together to exchange and share the latest results in research and application of Semantic Web and Ontology. The mini-track will provide a forum for gaining a better understanding of these new technologies and their business aspects. Potential authors/researchers are encouraged to submit papers that address the issues related to designing, developing, and evaluating Semantic Web/Ontology from the technical, behavioral, economical, or managerial perspectives.

Social Media Analytics - Methods and Technologies

Stefan Stieglitz, University of Münster, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Axel Bruns, Queensland University of Technology, This e-mail address is being protected from spambots. You need JavaScript enabled to view it

 

According to Zeng et al. (2010), social media analytics is supposed to provide tools and frameworks to collect, monitor, analyze, summarize, and visualize social media data in an automated way due to the massive amount of (mostly unstructured) social media data. Methods of social media analytics are e.g. automatic content analysis, machine learning, sentiment analysis, manual content analysis, social network analysis, and genre analysis. Currently there exists a wide spectrum of proprietary tools as well as open source software which help researchers to gather and analyze social media data. However, researchers still have to face several technical or methodological problems, e.g. changing APIs, intransparent software, and inaccurate automatic content analysis. At the same time there is a lack of frameworks describing systematic approaches and appropriate methods and techniques required for tracking, monitoring and analyzing content from social media in different contexts.

The goal of this minitrack is to provide a forum for academics and practitioners to identify and explore the methodological and technical issues of social media analytics. Empirical (both quantitative and qualitative) as well as theoretical work is welcome.