International Journal of Web Science
- Editor in Chief
- Associate Prof. Shangguang Wang
- ISSN online
- ISSN print
- 4 issues per year
IJWS is a refereed scientific international journal. It aims to improve the state-of-the-art of worldwide research in the areas of web theories, services, applications and standards by publishing high-quality papers in this area. IJWS is committed to deepening the understanding of enabling theories and technologies for applying and developing the Web as a global information repository.
Topics covered include
- Virtual reality
- Internet finance
- Internet of things
- Cloud computing
- Social networking
- Internet of vehicles
- Edge/fog computing
- Security, trust, privacy
- Cyber-physical systems
- Big data and databases
- Simulation/experimental tools
- Web searching and data mining
- Semantic Web, Web applications
- Network infrastructures and performance
- Web/services computing, mobile/pervasive computing
The objectives of IJWS are to present and stimulate the advances of new theories, the future development of new models, new methodologies and new tools for building a variety of embodiments of web-based systems and applications. The journal also aims to establish an effective channel of communication between decision makers, academic and research institutions and persons concerned with the academic research and practical deployment of web science. IJWS provides a high-quality platform for this purpose.
IJWS provides a vehicle to help professionals, academics, researchers and policy makers working in the fields of web theories, services, applications, standards and tools to disseminate information and to learn from each other's work.
IJWS is devoted to the publication of high quality papers on theoretical developments and practical applications in web science. Original research papers, state-of-the-art reviews and technical notes are invited for publication. Special attention will be given to papers focusing on new advances in web theories and technologies. Special Issues devoted to important topics in web science and technologies will occasionally be published.
Editor in Chief
- Wang, Shangguang, Beijing University of Posts and Telecommunications, China
- Leung, Victor C. M., The University of British Columbia, Canada
- Shojafar, Mohammad, University of Surrey, UK
- Trunfio, Paolo, University of Calabria, Italy
- Apduhan, Bernady O., Kyushu Sangyo University, Japan
- Aversa, Rocco, Second University of Naples, Italy
- Chen, Liang, Sun Yat-Sen University, China
- Wong, Kok-Seng, Soongsil University, South Korea
- Zhou, Ao, Beijing University of Posts and Telecommunications, China
Editorial Board Members
- Bhatt, Chintan, Charotar University of Science and Technology, India
- D'Mello, Demian Antony, St. Joseph Engineering College , India
- Mcheick, Hamid, Université du Québec à Chicoutimi, Canada
- Upadhyay, Nitin, Goa Institute of Management, India
A few essentials for publishing in this journal
- Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
- Conference papers may only be submitted if the paper has been completely re-written (more details available here) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
- Briefs and research notes are not published in this journal.
- All our articles go through a double-blind review process.
- All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
- There are no charges for publishing with Inderscience, unless you require your article to be Open Access (OA). You can find more information on OA here.
- All articles for this journal must be submitted using our online submissions system.
- View Author guidelines.
Musical algorithm classifies classics
23 May, 2022
An efficient neural network can now take a series of music files as input and define them quickly by genre and style, thanks to work published in the International Journal of Web Services. Such a system could be a boon to music streaming services that hope to offer their users an effective recommendation system to allow them to access novel music they may enjoy as much as their old favourites... Jagendra Singh of the School of Computer Science Engineering and Technology at Bennett University in Greater Noida, India, has tested the system against six types of music, including jazz, hip-hop, electronic, rock, classical, and folk and found it to be effective. The algorithm performs even better when the spectrographic frequency of the sounds and the time sequence pattern are incorporated as variables into their hybrid recommendation system [...]More details...