Submission Due Date
5/10/2022
Guest Editors
Aleksandar Karadimche, University of Information Science and Technology UIST "St. Paul the Apostle," Republic of Macedonia
Reshu Agarwal, AIIT, Amity University, India
Xiaoqing Yin, National University of Defense Technology, China
Introduction
With the rapid development of various information and communication technologies, more and more data are generated from massive information platforms, such as instant messenger, e-mail, online education platforms, teleconferencing suites, social media platforms and the Internet of Things (IoT). In some information platforms, the data are produced from massively distributed nodes, especially the web-based platforms and the Internet of Things. Imp r o v i n g the quality of service (QoS) and quality of experience (QoE) is a critical and emergent issue in these platforms. E- collaboration technologies make the applications and services based on distributed information platforms possible. However, it still meets how to mine minor critical information among massive data to implement the applications and services to be intelligent. According to the learnt model, pattern recognition and mining can find common behaviours from massive historical data and predict users' future behaviours. Combining collaborative learning and pattern mining can significantly improve the QoS and QoE of the information platforms.
Objective
This special issue is expected to spur further research and development of a combination of collaborative learning and automatic pattern mining to enhance and implement intelligent information platforms. It will provide a unique opportunity for researchers in academia and practitioners in the industry to contribute their recent works about collaborative learning and automatic pattern mining based intelligent applications.
Recommended Topics
Novel architecture, algorithms, model and protocol designs for intelligent information platforms
Collaborative learning paradigm towards intelligent information platform
Collaborative learning paradigm based on emerging sensing and collecting technologies
Collaborative learning, data mining, statistical modeling, and machine learning for intelligent information platforms
Automatic pattern mining and recognition algorithms for intelligent information platforms
AI-based networking and computing approaches in intelligent information platforms
Collaboration technologies for smart applications, e.g., instant messenger, e-mail, online education platform, teleconferencing suites, social media platform and Internet of Things (IoT)
AI-based solutions for intelligent information platforms, such as smart sensors, wearables devices, web of things
Data-centric management for intelligent information platforms
Other smart applications based on collective learning or AI in intelligent information platforms
Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Collaborative Learning and Automatic Pattern Mining to Support Intelligent Information Platforms on or before May 10th, 2022. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.
All inquiries should be directed to the attention of:
Aleksandar Karadimche
Reshu Agarwal
Xiaoqing Yin Guest Editors International Journal of eCollaboration (IJeC) Email: aleksandar.karadimce@uist.edu.mk; agarwal.reshu3@gmail.com; yinxiaoqing89@gmail.com
I'm inviting you to publish in this highly reputable International Journal of eCollaboration (IJeC)
Assistant Professor, Aleksandar Karadimche, PhD
Faculty of Information and Communication Sciences
University of Information Science and Technology “St. Paul the Apostle”- Ohrid
From Aleksandar Karadimce
Today's most popular social networks, such as Facebook, Twitter, etc., are centralised platforms owned by private corporations that unilaterally control the respective networks. International project "smART socIal media eCOsystem in a blockchaiN Federated environment (ARTICONF)" is devoted to researching and developing a series of trustworthy, resilient and globally sustainable decentralised social network platforms. Today, social media platforms are key technologies that connect people to global networks. They can create new forms of communication and bring about significant changes in mobilisation, business practices, the learning process and the acquisition of knowledge. Market companies currently carry significant social responsibility. They are not affected in many respects, including trust and concern for social media user data privacy.
Essentially, ARTICONF aims to create a decentralised and federated social media ecosystem, supported by an underlying blockchain technology seamlessly coupled with optimised trust-based measures in an anonymised environment, which simplifies traceability to identify bad actors and eliminates malicious contents such as fake news. Moreover, it's novel socio-cognitive, and smart matching practices integrate relevant users with common interests into an orchestrated networked community world without de-anonymising them. Supposedly, such a design would bring a range of social media actors (individuals, start-ups, SMEs) under one systemic umbrella and allow them to be a part of incentivised collaborative decision-making and sharing economy. In principle, ARTICONF presents a new perspective in the current age when data breaches and undemocratic practices are a regular phenomenon at the hands of centralised intermediaries, by creating an open and transparent ecosystem, where control lies in the hands of each anonymous user with provisions for individual or collaborative monetised enhancement.
The University of Information Sciences and Technologies "St. Paul the Apostle" from Ohrid is the carrier of the scientific research work for dynamic analytics and knowledge of the data obtained from the participants' joint cooperation in the smart ecosystems from social media. The main task will be to make aggregation, knowledge detection and experience based on interaction with users. Dr Aleksandar Karadimce, Assistant Professor at the University of Ohrid, is part of the team of researchers working on scientific research to develop interactive guided tools to improve users' monetised earnings of future decentralised social networks.
The three-year project, endowed with a budget of approx. 4.2 million Euros, brings together eight participating institutions from Austria, the Netherlands, Great Britain, North Macedonia, Portugal, Spain, and Norway. More information on the institutions involved in the development of the project and the scientific research achievements is available on the project website https://articonf.eu/.
