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Journal of Intelligent Information Systems

Integrating Artificial Intelligence and Database Technologies

Publishing model:

Aims and scope

The mission of the Journal of Intelligent Information Systems: Integrating Artifical Intelligence and Database Technologies is to foster and present research and development results focused on the integration of artificial intelligence and database technologies to create next generation information systems - Intelligent Information Systems. 

These new information systems embody knowledge that allows them to exhibit intelligent behavior, cooperate with users and other systems in problem solving, discovery, access, retrieval and manipulation of a wide variety of multimedia data and knowledge, and reason under uncertainty. Increasingly, knowledge-directed inference processes are being used to:

discover knowledge from large data collections,
provide cooperative support to users in complex query formulation and refinement,
access, retrieve, store and manage large collections of multimedia data and knowledge,
integrate information from multiple heterogeneous data and knowledge sources, and
reason about information under uncertain conditions.


Multimedia and hypermedia information systems now operate on a global scale over the Internet, and new tools and techniques are needed to manage these dynamic and evolving information spaces.

The Journal of Intelligent Information Systems provides a forum wherein academics, researchers and practitioners may publish high-quality, original and state-of-the-art papers describing theoretical aspects, systems architectures, analysis and design tools and techniques, and implementation experiences in intelligent information systems. The categories of papers published by JIIS include: research papers, invited papters, meetings, workshop and conference annoucements and reports, survey and tutorial articles, and book reviews. Short articles describing open problems or their solutions are also welcome.

Topics of Interest:

Topics of interest to JIIS include, but are not limited to:

Foundations and principles of data, information, and knowledge models,
Methodologies for IIS analysis, design, implementation, validation, maintenance and evolution,
User models, intelligent and cooperative query languages and interfaces,
Knowledge representation, integration, fusion, interchange and evolution,
Intelligent information retrieval, digital libraries, and networked information retrieval,
Distributed multimedia and hypermedia information space design, implementation and navigation,
Visual interfaces, visual query languages, and visual expressiveness of IIS,
Machine learning, knowledge discovery, and data mining,
Uncertainty management and reasoning under uncertainty,
Applications and case studies in novel applications (e.g., global change, scientific databases, Human Genome project, Earth Observing System, manufacturing, telemedicine, education, etc.)


We seek papers that improve on the best academic research or the best industrial practice. Submitted papers should be motivated by the problems they address with compelling examples from real or potential applications. Systems papers must contain interpreted experimentation results either on real systems or simulations based on representative traces from real systems. Papers from industrial organizations that discuss implementation of systems and their use in practice are welcome. Proposals for special issues, especially on emerging topics, are also welcome.

Authors can expect a first decision response in three months from their manuscript's submission date.

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