Knowledge and Information Systems - Call for Survey Papers

Knowledge and Information Systems (http://kais.bigke.org/ (this opens in a new tab)) seeks to publish survey papers on areas covered by the journal.

A survey paper, whether invited or not, should normally contain a historical perspective on the research and development up to the current date as well as information about the state of the art. This paper should be a comprehensive survey of an individual stance on the topic: the description of existing work should be structured and should include discussions (for example, comparative methods). It should not be a simple juxtaposition of summaries or groups of papers. Although the author’s own work may sometimes be an important part of the investigation, there should be no major prejudice against it: the work of others should be mentioned and appreciated based on its relevance and importance. The paper should strive to provide clear perspectives, and should be of high quality in presentation (including examples) and appropriate technical level, and should be based on existing literature.

The journal welcomes surveys that cover more than one area and that seek to show relationships between them, such as opportunities for and obstacles to using the techniques of one area to help another. For example, the areas could be learning on the one hand and multi-agent systems on the other. All the areas should normally be within the coverage of the journal, but exceptions can be made.

It is crucial that a survey paper be written in such a way that it is mostly accessible to professionals in knowledge and information systems who do not have a detailed knowledge of the area(s) reviewed. However, it may also contain a limited amount of technical material that is only likely to be accessible to experts in the area(s).

Please select Survey as the Article Type when submitting on KAIS submission website (this opens in a new tab) ( https://www.editorialmanager.com/kais/ (this opens in a new tab) ). Survey papers should be prepared according to the guidelines for ordinary submissions. More details can be found at http://kais.bigke.org/ (this opens in a new tab).

Contact Details

Prof. Shuiguang Deng
College of Computer Science and Technology
Zhejiang University, Hangzhou 310027, China
dengsg@zju.edu.cn; deng.terry@gmail.com
Tel: +86-0571-88273422 ; Mobile: +86 13605712329
Homepage: http://mypage.zju.edu.cn/shuiguang (this opens in a new tab)