Unlocking Minds and Machines: Advances in Cognitive Computing and Big Data Analytics
A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).
Deadline for manuscript submissions: 31 December 2024 | Viewed by 297
Special Issue Editors
Interests: XAI for deep learning; concept learning; NLP; high-dimensional data; computational statistics; probabilistic methods in combinatorics; statistical inference
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue aims to explore the intersection of cognitive computing, machine learning, and big data analytics. It delves into advanced AI techniques that mimic human cognitive functions, such as natural language processing (NLP), facial expression recognition, and other cognitive tasks. The focus is on leveraging these techniques to extract insights from massive datasets, enabling innovative applications in various domains.
The topics covered in this Special Issue include, but are not limited to, the following:
- Advanced NLP techniques for processing and analyzing textual data;
- Facial expression recognition and emotion analysis using deep learning;
- Cognitive computing applications in healthcare, finance, marketing, and other industries;
- Big data analytics methodologies for processing and extracting insights from large datasets;
- The integration of cognitive computing and big data technologies for developing intelligent systems.
The purpose of this Special Issue is to provide a platform for researchers and practitioners to share their latest findings, innovations, and best practices in the field of cognitive computing and big data. It aims to foster collaboration and discussion among experts from academia, industry, and government agencies to address the challenges and opportunities in this rapidly evolving field.
This Special Issue will complement existing literature by providing a comprehensive overview of recent advancements in cognitive computing and big data analytics; offering insights into the practical applications of AI technologies in solving real-world problems; identifying emerging trends and future research directions in the field; and highlighting the importance of interdisciplinary research in cognitive computing, big data, and machine learning. This Special Issue aims to contribute significantly to the growing body of knowledge in cognitive computing and big data analytics, ultimately advancing the field and benefiting society as a whole.
Dr. Dan Vilenchik
Dr. Havana Rika
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. 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.
Keywords
- cognitive computing
- big data analytics
- natural language processing (NLP)
- facial expression recognition
- human–computer interaction
- emotion analysis
- text analytics
- intelligent systems
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