[AISWorld] AMCIS 2014 - Call for Papers, Track Name: Intelligence and Intelligent Systems

[Vijayan Sugumaran]

Call for Papers

 

19th Americas Conference on Information Systems

Savannah, GA, August 7-10, 2014

 

Track Name: Intelligence and Intelligent Systems (Sponsored by SIGODIS)

http://amcis2014.aisnet.org/index.php/track-list/77-amcis-2014/101

 

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). 

 

The following mini-tracks are part of this track:


1. Application of Intelligent Agent and Multi-Agent Systems


2. Modelling for Agents and Services


3. Semantic Technologies and Big Data Analytics


4. Web and Social Intelligence


5. Customer Experience and Organizational Intelligence


 


Submit your manuscript before March 1, 2014 at
http://mc.manuscriptcentral.com/amcis2014 

 

Important dates: 

March 1, 2014     Submission Deadline

April 4, 2014       Author Notification

April 18, 2014     Revision Deadline

April 25, 2014      Camera Ready Submission Deadline

 

A brief description of each mini-track follows.

 


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


 


Vijayan Sugumaran, Oakland University, sugumara at oakland.edu

Stefan Kirn, Universitat Hohenheim, Stefan.kirn at uni-hohenheim.de

 

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).

 


Suggested Topics (not exhaustive)


·         Application of intelligent agent and multi-agent systems in
different domains

·         Distributed Intelligent Systems

·         Agent communication, collaboration, and coordination

·         Agents and web data mining

·         Multi-agent technology and grid computing

·         Architectures, environments and languages for e-commerce agents

·         Automated shopping and trading agents

·         Agent-based auction, negotiation and decision making

·         Agent building tools and environments

·         Agent driven interoperability and distributed decision support

·         Software agents and knowledge management

·         Agent-based Business Analytics

·         Business Intelligence and multi-agent systems

·         Intelligent technologies for big data analytics

 


Mini-Track: Modelling for Agents and Services


 


Ghassan Beydoun, University of Wollongong, beydoun at uow.edu.au

Rubén Fuentes, Universidad Complutense de Madrid, Spain, ruben at fdi.ucm.es

Dongming Xu, University of Queensland, Australia, d.xu at business.uq.edu.au

 

The objective of this mini-track is to encourage and renew research in
agents and service-based systems with an emphasis on the modeling
perspective on these systems. 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.

 


Suggested Topics (not exhaustive)


·         Agent-based services

·         Agent models and ontology in service science

·         Applications of agent models

·         Agent oriented software engineering trends

·         Service modeling trends

·         Service systems development and practice in different domains:
Healthcare, financial, government, agriculture, education, entertainment,
etc.

·         Service requirements analysis, modeling and design

·         Service design methodologies and related software patterns

·         Evaluation of agent and service models



Mini-Track on Semantic Technologies and Big Data Analytics


 


Victoria Yoon, Virginia Commonwealth University, vyyoon at vcu.edu
Richard Redmond, Virginia Commonwealth University,
<mailto:rredmond at vcu.edu> rredmond at vcu.edu 

 

The semantic heterogeneity among excessive volume of diverse data imposes a
serious challenge for big data analytics. This mini-track aims to bring
academicians and practitioners together to exchange and share the latest
results in research and application of Semantic Integration for Big Data
Analytics. The mini-track will provide a forum for gaining a better
understanding of the new technologies and their business aspects for
semantic integration for big data analytics.

 


Suggested Topics (not exhaustive)


·         Semantic interoperability

·         Innovative design artifacts for semantic integration

·         Novel applications for semantic integration for Big Data Analytics

·         Semantic Integration for e-business and e-learning

·         Semantic Web/Ontology for Data Integration

·         Ontology creation, evolution, reconciliation, and mediation for
Big Data Analytics

·         Ontology mapping, Integration, and/or alignment for Big Data
Analytics

·         Software agents for Semantic Integration

·         Managerial Issues of Semantic Integration for Big Data Analytics


 


Mini-Track: Web and Social Intelligence


 


Donald Heath, UNC Greensboro,  <mailto:drheath2 at uncg.edu> drheath2 at uncg.edu

Jai Ganesh, Cognizant, India, jaiaiyar at yahoo.com

Rahul Singh UNC Greensboro, r_singh2 at uncg.edu

 

Enterprises are increasingly exploring Social Media Strategies to identify
and engage their end customers and build competitive differentiation.
Content generated in social networking environments would include discussion
threads, logs of chat room conversations, contents of blogs, and any other
content posted by users. The accumulated content and ideas within successful
social networking environments thus becomes an aggregation of the collective
intelligence of the user community participating in those sites. The
accumulated content can be considered as an asset that has value, which can
be tapped through the right types of analyses. This asset has potential
value to both owners of the sites as well as the organizations whose
products and services being discussed It presents significant implications
for enterprises wanting to leverage social networks to draw insights and
inferences on user participation and preferences expressed in networks.

 


Suggested Topics (not exhaustive)


·         Social Networks (Twitter, Linkedin, Youtube, Discussion Forums)

·         Social Recommender Systems

·         Internal & External Social Media Strategies of enterprises

·         Message propagation  in Social Networks

·         Social Movements

·         Crowd sourcing

·         Opinion mining

·         Social network analysis

·         Organizational Network Analysis

·         Innovative collaborative business models based on Social Media

*	Social Media enabled value creation strategies
*	Social Media based business value Webs


 


Mini-Track: Customer Experience and Organizational Intelligence


 


Jai Ganesh, Cognizant, India, jaiaiyar at yahoo.com

Donald Heath, UNC Greensboro, drheath2 at uncg.edu

Rahul Singh, UNC Greensboro, r_singh2 at uncg.edu

 

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.

 


Suggested Topics (not exhaustive)


·         Engage end customers via multitude of devices and delivery
channels

·         Multi-modal user experiences & Immersive Interaction Technologies

·         Enhance customer engagement by combining immersive interaction
technologies and multi-modal user experiences

·         Enable enterprises to make intelligent decisions related to
workforce composition, collaboration, leadership and, employee retention

*	Pervasive computing devices requiring the need to reach end
customers across multitude of devices
*	Exponential growth of  data (both structured as well as
unstructured), created by end customers, sensors etc. requiring the need to
analyses and visualize the data 
*	Leveraging easy availability of computing power on the go in the
form of cloud computing  
*	Decision making by understanding and analyzing the collective
intelligence created across various customer touch points as well as social
networks.
*	Better understanding of customer behavior using techniques such as
text analytics, natural language processing as well as social network
analysis. 
*	Improved visibility across the supply chain and real-time data
availability.


 


 

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