Journal Information
Information Sciences
http://www.journals.elsevier.com/information-sciences/
Impact Factor:
4.832
Publisher:
ELSEVIER
ISSN:
0020-0255
Viewed:
9389
Tracked:
23

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Call For Papers
Information Sciences will publish original, innovative and creative research results. A smaller number of timely tutorial and surveying contributions will be published from time to time.

The journal is designed to serve researchers, developers, managers, strategic planners, graduate students and others interested in state-of-the art research activities in information, knowledge engineering and intelligent systems. Readers are assumed to have a common interest in information science, but with diverse backgrounds in fields such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioural sciences and biochemistry.

The journal publishes high-quality, refereed articles. It emphasizes a balanced coverage of both theory and practice. It fully acknowledges and vividly promotes a breadth of the discipline of Informations Sciences.

Topics include:

Foundations of Information Science:
Information Theory, Mathematical Linguistics, Automata Theory, Cognitive Science, Theories of Qualitative Behaviour, Artificial Intelligence, Computational Intelligence, Soft Computing, Semiotics, Computational Biology and Bio-informatics.

Implementations and Information Technology:
Intelligent Systems, Genetic Algorithms and Modelling, Fuzzy Logic and Approximate Reasoning, Artificial Neural Networks, Expert and Decision Support Systems, Learning and Evolutionary Computing, Expert and Decision Support Systems, Learning and Evolutionary Computing, Biometrics, Moleculoid Nanocomputing, Self-adaptation and Self-organisational Systems, Data Engineering, Data Fusion, Information and Knowledge, Adaptive ad Supervisory Control, Discrete Event Systems, Symbolic / Numeric and Statistical Techniques, Perceptions and Pattern Recognition, Design of Algorithms, Software Design, Computer Systems and Architecture Evaluations and Tools, Human-Computer Interface, Computer Communication Networks and Modelling and Computing with Words

Applications:
Manufacturing, Automation and Mobile Robots, Virtual Reality, Image Processing and Computer Vision Systems, Photonics Networks, Genomics and Bioinformatics, Brain Mapping, Language and Search Engine Design, User-friendly Man Machine Interface, Data Compression and Text Abstraction and Summarization, Virtual Reality, Finance and Economics Modelling and Optimisation
Last updated by Xin Yao in 2017-08-21
Special Issues
Special Issue on Business Analytics – Emerging Trends and Challenges
Submission Date: 2018-03-30

We are living in a world characterized by an abundance of many different kinds of data. The importance of analyzing information contained therein has been already recognized by academia and practitioners. As a result, we have witnessed a rapidly growing number of products and solutions by the respective solution providers. What is still missing, however, is an adequate interpretation and modeling of the ever growing data sets to create intelligent systems that are able to propose advanced solutions to complex problems. As a consequence, this special issue aims at moving towards the next step and foster the development of advanced techniques coming from machine learning, artificial intelligence, uncertainty modeling, and data science, among others, to establish emerging trends in business analytics capable of facing the current challenges. In this special issue we understand the term “Business Analytics” in a rather broad sense, covering a spectrum of different application areas. Topics relevant for this special issue include, but are not limited to: - Business Analytics for Financial Modeling - Forecasting - Human Resources (HR) Analytics - Healthcare Analytics - Learning Analytics - Fraud Detection and Cybersecurity - Privacy-preserving and ethics in Business Analytics
Last updated by Dou Sun in 2017-11-04
Special Issue on Business Analytics – Emerging Trends and Challenges
Submission Date: 2018-03-30

We are living in a world characterized by an abundance of many different kinds of data. The importance of analyzing information contained therein has been already recognized by academia and practitioners. As a result, we have witnessed a rapidly growing number of products and solutions by the respective solution providers. What is still missing, however, is an adequate interpretation and modeling of the ever growing data sets to create intelligent systems that are able to propose advanced solutions to complex problems. As a consequence, this special issue aims at moving towards the next step and foster the development of advanced techniques coming from machine learning, artificial intelligence, uncertainty modeling, and data science, among others, to establish emerging trends in business analytics capable of facing the current challenges. In this special issue we understand the term “Business Analytics” in a rather broad sense, covering a spectrum of different application areas. Topics relevant for this special issue include, but are not limited to: - Business Analytics for Financial Modeling - Forecasting - Human Resources (HR) Analytics - Healthcare Analytics - Learning Analytics - Fraud Detection and Cybersecurity - Privacy-preserving and ethics in Business Analytics
Last updated by Dou Sun in 2017-11-04
Special Issue on Privacy Computing: Principles and Applications
Submission Date: 2018-05-30

While more and more data including personal information is being hosted online such as cloud infrastructure, privacy leakage is becoming one of most challenging concerns in information collection, sharing or analysis. In practice, different temporal, spatial or application cases often demand different privacy protection solutions. Accordingly, most of traditional approaches are case by case or based on a specific application circumstance. It is on demand for a systematic and quantized privacy characterization towards systematic computing model describing the relationships between protection level, profit and loss as well as the complexity of integrated privacy protection models because real-world applications with privacy are changing across time, space and different domains. This special issue focuses on the new paradigm of privacy computing for principles and applications. High quality publications are solicited from engineers and scientists in academia, industry, and government to address the resulting profound challenges on principles and applications of privacy computing. Topics of interests include, but are not limited to: - Fundamental principles for privacy computing - Privacy principles for information sensing, collection, engineering and distribution - Privacy protection based information hiding and sharing principles - Privacy preserving data publishing principles - Privacy information integration, synergy and storage - Privacy operation and modelling methodologies - Privacy protection methodologies and principles - Privacy applications in cloud, social networks, IoT and Industrial Internet - Privacy, security, trust, autonomy, reliability, fault-tolerance – association principles - Privacy, AI, Machine Learning, Data Mining and Knowledge Discovery – association principles
Last updated by Dou Sun in 2017-11-04
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