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COMSIS 2016 : Knowledge-based industrial applications

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Link: http://www.comsis.org/
 
When N/A
Where N/A
Submission Deadline Feb 1, 2016
Notification Due Jul 31, 2016
Final Version Due Sep 15, 2016
Categories    knowledge representation and   knowledge acquisition in indus   decision-support mechanisms   software to modeling knowled
 

Call For Papers

Computer Science & Information Systems

ISSN: 1820-0214 (Print) 2406-1018 (Online).

2014 ISI Impact Factor: 0.477

http://www.comsis.org/

Knowledge-based industrial applications

Knowledge-based technologies are gaining momentum and they are currently

achieving a certain degree of maturity. They are especially valuable in situations in

which the amount of available information is prohibitive for the intuition of an

unaided human decision maker and in which precision and optimality are of

importance. Knowledge-based systems can aid human cognitive deficiencies by

integrating various sources of information, providing intelligent access to relevant

knowledge, and aiding the process of structuring decisions. They can also support

choice among well-defined alternatives and build on formal approaches, such as the

methods of engineering economics, operations research, statistics analysis, and

decision theory. They can also employ artificial intelligence methods to address

heuristically problems that are intractable by formal techniques. They provide a

consistent and reliable basis to face the challenges for organization, manipulation and

visualization of the data and knowledge, playing a crucial role as the technological

basis of the development of a large number of Computational Intelligence Systems.

These technologies draw on standard and novel techniques from various disciplines

within Computer Science, including Knowledge Engineering, Natural Language

Processing, Decision Support Systems, Artificial Intelligence, Databases, Software

Agents, etc. The methods and tools developed and integrated for this purpose are

generic and have a very large application potential in a large amounts of fields like

Information Retrieval, Semantic Searches, Information Integration, Information

Interoperability, Bioinformatics, eHealth, eLearning, Software Engineering,

eCommerce, eGovernment, Social Networks, eSupply Chain, etc.

The design tools for management knowledge allow the industry to improve and learn

from the experiences of their activities and employees. This Special Issue considers the

following industrial sectors, but are not limited: Aerospace, Agriculture, Automotive,

Banking, Business Services, Food Manufacturing, Mining and Mineral Extraction,

National Government, Insurance, Energy Services and others.

The goal of the Special Issue is to investigate and disseminate trends among innovative

and high-quality research regarding the implementation of conceptual frameworks,

strategies, techniques, methodologies, informatics platforms and models for

developing advanced Knowledge-based methods and techniques and their application

in industry. Every paper must report a proposal or application in industry.

Topics of interest in this workshop include, but are not restricted to:

• Knowledge Representation and Reasoning in industry

• Knowledge Acquisition in industry

• Knowledge-Based Implementation techniques and System Architectures

• Application of Knowledge-Based Methods

• Software Tools for Knowledge-Based Systems construction

• Knowledge Acquisition & Representation

• Ontological Engineering in industry

• Ontology Sharing and Reuse in industry

• Ontology Matching and Alignment in industry

• Semantic Web Semantic Integration of heterogeneous data sources

• Natural Language Processing in industry

• Social Semantic Web

• Knowledge-based Decision Support Systems in industry

• Industrial linked Data Applications

• Supply Chain Knowledge Management

• Decision-Support mechanisms

• Knowledge, Industry and Environment

• Tools for Industrial Knowledge Management

• Software to Modeling Knowledge in industry

• Industrial applications and Case-studies

Submission procedure

Papers submitted must have not been published previously or under consideration for

publication in other journals, though they may represent significant extensions of prior

work. Authors should submit their paper via email: valencia@um.es,

jorge.garcia@uacj.mx, galor@itorizaba.edu.mx and csanchez@itorizaba.edu.mx, and the

subject of the email should be: “COMSIS SI Submission: KB applications”. In a first

stage a preliminary selection of the submitted papers will be done by guest editors.

Then authors will be notified if their paper has been selected a possible candidate to be

published in two weeks.

Then, all preselected submissions should be submitted through the submission

platform. They will be peer-reviewed following the double-blind review process. The

objective is to apply very high standards of acceptance while ensuring fair, timely and

efficient review cycles.

The acceptance process will focus on papers that address original scientific

contributions in the form of theoretical and experimental research and case studies

applying advanced Knowledge-based methods and techniques and their application in

industry. Also, an abstract submission is mandatory to allow editors the assignment of

the most suitable reviewers for each paper.

Working schedule

• Submission deadline: February 1st, 2016

• First selection of submissions; February 15th, 2016

• Completion of first‐round reviews: May 15th, 2016

• Revised papers: July 31st, 2016

• Target of the second (last) round of reviews: September, 15h, 2016

• Publication (tentative): End of 2016

Special Issue Editors

Rafael Valencia-García, Universidad de Murcia, Spain (valencia@um.es)

Jorge Luis Garcia-Alcaraz, Autonomous University of Ciudad Juarez, México

(jorge.garcia@uacj.mx)

Giner Alor-Hernández, Instituto Tecnológico de Orizaba, México

(galor@itorizaba.edu.mx )

Cuauhtemoc Sanchez-Ramirez, Instituto Tecnológico de Orizaba, México

(csanchez@itorizaba.edu.mx)

Related Resources

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ECBS 2017   5th European Conference on the Engineering of Computer Based Systems
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