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SIIFT-SBD 2014 : Special Issue on Information Fusion Technologies for Social Big Data | |||||||||||
Link: http://www.journals.elsevier.com/information-fusion/call-for-papers/information-fusion-technologies-for-social-big-data/ | |||||||||||
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Call For Papers | |||||||||||
Special Issue on Information Fusion Technologies for Social Big Data
The Information Fusion Journal is planning a special issue onInformation Fusion Technologies for Social Big Data. Social networking services are strongly related to the “Big Data” issues. As we have vari-ous types of feasible information from “Big Data” sources, e.g., medical records, bioinfor-matics, and social media, it is becoming increasingly more difficult to efficiently develop social networking services. Efficient information management remains a challenge in many research areas, e.g., knowledge acquisition, reuse evaluation as well as integration. Also, given the number of diverse information fusion system architectures that are involved in these areas, they need to exploit relevant solutions to support a number of intelligent services (e.g., knowledge management and decision making). In this special issue, we plan to focus on various research and application issues in large-scale social networks built around a variety of intelligent systems. The aim of this issue is to bring together researchers and practitioners in areas of information management and knowledge-based systems to share their research achievements and experiences which explicitly involve information fusion concepts and techniques. Manuscripts (which should be original and not previously published either in full or in part or presented even in a more or less similar form at any other forum) covering unpublished research in processing and analyzing social big data that clearly delineate the role of information fusion in the context of intelligent social services are invited. The manuscript will be judged solely on the basis of new contributions excluding the contributions made in earlier publications. Contributions should be described in sufficient detail to be reproducible on the basis of the material presented in the paper and the references cited therein. Topics appropriate for this special issue include (but are not necessarily limited to): • Multiple and Distributed Information Fusion Architectures for Social Big Data • Knowledge management and discovery with Social Big Data • LOD and Ontology Management with Social Big Data • Integration of KBS by using Social Big Data • Knowledge inconsistency on distributed computing • Database and Information Retrieval Systems by using Social Big Data • Ubiquitous and Mobile Services by Social Big Data • Intelligent Multimedia systems by Social Big Data • Information modeling and requirements engineering • Intelligent agents and agent-based applications for Social Big Data • Computational and Collective Intelligence for Social Big data • Web databases and web-based multimedia systems • Various KBS applications with Social Big Data • Distributed knowledge fusion and analysis for Social Big Data Manuscripts should be submitted electronically online at http://ees.elsevier.com/inffus The corresponding author will have to create a user profile if one has not been estab-lished before at Elsevier. Guest Editor(s) Jason J. Jung, j2jung@gmail.com, Yeungnam University, Korea David Camacho, david.camacho@uam.es, Universidad Autónoma de Madrid, Spain Deadline for Submission: November 15, 2014 |
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