Feature-Rich Artificial Intelligence Models and Applications of Cognition

Dear Colleagues,

Artificial intelligence (AI) is a rapidly growing trend within cognitive sciences, with fields such as natural language processing, data mining and cognitive network science quickly revolutionizing how we build models of knowledge processing and understanding. To sustain this growth, there is an urgent need for next-generation models capable of managing multiple structural, associative, vectorial and qualitative patterns at once.

Feature-rich models are particularly promising, because they can simultaneously merge networks and non-network information among attributes on nodes, categories of connections or dynamic features. Feature-rich cognitive mining can result in the extraction of new knowledge that a classic network, data mining or natural language approaches alone could not highlight.

This Special Issue hopes to attract innovative publications regarding AI-based models grounded in feature-rich representations and of relevance for the investigation or simulation of cognition. Such methods can be inspired by the cognitive processing of knowledge, or display significant performance in cognition-related tasks, such as natural language understanding, text classification or word prediction tasks. In this Special Issue, we wish to include modeling approaches where feature-rich representations of data achieve significant performance boosts that would otherwise not be viable with other approaches or could not be easily interpreted within other modeling paradigms.

Potential topics include, but are not limited to, the following:

• Mining of feature-rich datasets and AI;
• Network science and AI for understanding cognitive representations;
• Network psychometrics and soft computing for understanding mental health;
• AI for exploration and exploitation processes in semantic search;
• Complex system approaches to knowledge/information modeling;
• AI for feature-rich stance detection;
• AI applications to classification over textual corpora in clinical settings;
• AI applications to classification over textual corpora in social media settings;
• Opinion dynamics modeling;
• Higher-order interactions and AI;
• Methods for feature-rich complex networks;
• Feature-rich community detection for cognitive networks;
• Spreading activation and semantic diffusion in feature-rich networks;
• Feature-rich word embedding representations;
• Bias, polarization and ideology identification from social debates;
• Psychometric features for automatic assessments of personality traits with AI.

Dr. Massimo Stella
Dr. Giulio Rossetti
Guest Editors
Salvatore Citraro
Guest Editor Assistant

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. Big Data and Cognitive Computing is an international peer-reviewed open access monthly 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 1800 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.

• feature-rich models
• artificial intelligence
• cognitive computing
• cognitive representations
• knowledge modelling
• feature-rich multivariate analysis
• measurements of psychological constructs