Complex Network Modeling in Artificial Intelligence Applications

Dear Colleagues,

We are pleased to announce the Special Issue “Complex Network Modeling in Artificial Intelligence Applications” is now open for contributions. At present, the combined modeling of complex networks and deep learning algorithms is a main topic in artificial intelligence research. The indicative structure of a complex network uncovers the black box of a deep learning algorithm, making their combined models more explainable and more suitable for applications in various fields, such as computer vision, natural language processing and speech recognition. Today, successfully combined models, such as the graph neural network and its multiple variants, have made great progress in addressing emerging complex tasks, such as multimodular representation, knowledge reasoning and interpretable decision making. However, there are still challenges that need to be solved, especially regarding risk identification in finance, estimations of heterogenous treatment effects in marketing, smart route optimization in operations research, etc. Better utilization of graph structures and integrating network properties into deep learning design would be effective ways to tackle such challenges.

This Special Issue is devoted to state-of-the-art developments in the combined modeling of complex networks and deep learning algorithms as well as their applications. All related contributions are welcome, particularly those considering novel structure design combining complex networks and deep learning algorithms, advances in link prediction, key node recognition, community detection using deep learning methods and combined models’ applications in finance, marketing, operations research and other areas of interest.

Prof. Dr. Yongli Li
Prof. Dr. Chong Wu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• artificial intelligence
• complex networks
• deep learning
• graph neural network
• novel structures design combining complex networks and deep learning
• link prediction, key node recognition and community detection
• applications in finance, marketing, operations research and other areas of interest