International Journal of Computational Systems Engineering
- Editor in Chief
- Prof. Valentina E. Balas
- ISSN online
- ISSN print
- 4 issues per year
IJCSysE is a fully refereed scholarly international journal that provides a forum for professionals, academics and researchers in the fields of computational algorithms, intelligent information systems, computer applications and other related areas of science and engineering. It focuses on the state-of-the-art of aspects of theoretical analysis and practical application with emphasis on computational methods and systems engineering.
Topics covered include
- Fuzzy systems, rough sets
- Evolutionary computation, neural networks
- Human-machine learning systems
- Knowledge discovery, data mining
- Approximate reasoning, artificial intelligence/expert systems
- Knowledge-based/management systems, decision support systems
- E-education/commerce/governance systems
- Social systems analysis, social computing
- Behavioural modelling
- Computer games, virtual reality, CAD
- Computer graphics/multimedia
- Computing practices/applications
- Software engineering/management
- Human-computer interaction
- Real-time systems
The objectives of IJCSysE are to establish an international forum to report latest developments from interdisciplinary computational algorithms, intelligent information systems and computer applications. It aims to encourage those emerging theories, techniques and applications which help to understand complex behaviours and patterns of all engineering and social systems
IJCSysE provides a vehicle to help professionals, academics and researchers working in the fields of science, technology, engineering and possibly social/education studies to disseminate information and to learn from each other's work.
IJCSysE publishes original papers, review papers, and occasional technical reports. Special Issues devoted to important topics in interdisciplinary computational algorithms, intelligent information systems and computer technology will occasionally be published.
Editor in Chief
- Balas, Valentina E., Aurel Vlaicu University of Arad, Romania
Regional Editor Asia Pacific
- Chen, Wu-Hua, Guangxi University, China
Regional Editor Europe
- Pintea, Camelia, Technical University of Cluj Napoca, Romania
Regional Editor Middle East
- Dey, Rajeeb, National Institute of Technology, Silchar, India
Regional Editor North America
- Modi, Bhuvan, AT&T, USA
Regional Editor Americas
- Oliveira, Gustavo H. C., Federal University of Paraná , Brazil
Editorial Board Members
- Al-Khannak, Rafid, Buckinghamshire New University, UK
- Alinejad-Rokny, Hamid, University of New South Wales, Australia
- Arif, Muhammad, University of Gujrat, Pakistan
- Behera, H. S., Veer Surendra Sai University of Technology (VSSUT), India
- Bhatnagar, Vishal, Ambedkar Institute of Advanced Communication Technologies and Research, India
- Connor, Andy, Auckland University of Technology, New Zealand
- Fan, You-Ping, Wuhan University, China
- Kuchaki Rafsanjani, Marjan, Shahid Bahonar University of Kerman, Iran
- Liao, Mingyu (Gloria), National Kaohsiung University of Applied Sciences, Taiwan, Province of China
- Mabrouk, Mai S., Misr University for Science and Technology, Egypt
- Mishra, Vimal, Government Girls Polytechnic , India
- Ozel, Cenap, Dokuz Eylul University, Turkey
- Pavone, Mario, University of Catania, Italy
- Raja, S.P., Vellore Institute of Technology, India
- Ratnayake, R.M. Chandima, University of Stavanger, Norway
- Sallam, Amer, University of Hyderabad, India
- Samui, Pijush, National Institute of Technology Patna, India
- Sangaiah, Arun Kumar, VIT University, India
- Sarkar, Joy Lal, Amrita Vishwa Vidyapetham, India
- Senthilkumar, Sukumar, Vellore Institute of Technology, India
- Shen, Yan-jun, Three Gorges University , China
- Singh, Jasvir, Guru Nanak Dev University, India
- Song, Li-Zhong, Naval University of Engineering, China
- Song, Zhuoyi, University of Sheffield, UK
- Stan, Sergiu-Dan, Technical University of Cluj-Napoca, Romania
- Verma, K.D., Shri Varshney College of Post Graduate Studies and Research, India
- Wang, Tony, University of West of England , UK
- Xiao, Shen-Zhong, Guangdong AIB College, China
- Xu, Jian-sheng, Chinese Academy of Sciences, China
- Yao, Qiong-hui, Naval University of Engineering, China
- Yu, Hui, Three Gorges University, China
- Yu, Zhou, University of Leeds, UK
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.
Long-tail music recommendation
11 March, 2022
Music recommendation systems commonly offer users songs that others have enjoyed in the genres that the user requests. This can lead to popular songs becoming more popular. However, it neglects the less well-known songs, the long-tail songs that users may well enjoy just as much but have less chance of hearing because of the way the recommendation algorithms work. New work in the International Journal of Computational Systems Engineering, offers an approach to a music recommendation system that neglects the popular in favour of the long-tail and so could open users to new music. M. Sunitha and T. Adilakshmi Vasavi of the College of Engineering in Hyderabad, India, have developed a multi-stage graph-based method and a K-nearest neighbours (KNN)-based method to identify long-tail songs and feed these new works to the system's users [...]More details...