Natural Language Processing Applications in Big Data
A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).
Deadline for manuscript submissions: 31 December 2024 | Viewed by 525
Special Issue Editors
Interests: natural language processing; machine learning; computational media analysis
Interests: social computing; misinformation detection; text representation learning
Interests: applying linguistic knowledge bases to fundamental NLP models, including LLMs; NLP/LLM applications in healthcare, and digital wellbeing; neuro-cognitive NLP and its application in affective analysis/misinformation detection based on text and multimodality data
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent developments in NLP, especially the application of large language models (LLMs), demonstrate the monumental shift in the ability of natural language processing (NLP) to analyse big data. However, there is still a significant gap between the theoretical advancements of NLP and their practical real-world applications. This Special Issue targets the practical application of natural language processing (NLP) in different disciplines and delves into how NLP enhances data analysis, decision making, and productivity across various sectors (such as finance, healthcare, and marketing) by automating and improving processes.
The aim of this Special Issue is to highlight the impact of NLP on data analysis across disciplines and address the critical challenges of big data, such as computational efficiency and cost, explainability, low-resource language applications, and sustainable development that meets the growing needs of industry.
Relevant topics for this Special Issue include, but are not limited to, the following areas:
- Computational social science and cultural analytics;
- Dialogue and interactive systems;
- Efficient/low-resource methods for NLP;
- Ethics, bias, and fairness;
- Finance NLP;
- Generation;
- Healthcare NLP;
- Information extraction;
- Information retrieval and text mining;
- Interpretability and analysis of models for NLP;
- Legal NLP;
- Linguistic theories, cognitive modelling, and psycholinguistics;
- Machine learning for NLP;
- Machine translation;
- Multilinguality and language diversity;
- Multimodality and language grounding to vision, robotics, and beyond;
- Question answering;
- Resources and evaluation;
- Sentiment analysis, stylistic analysis, and argument mining;
- Speech recognition, text-to-speech conversion, and spoken language understanding;
- Summarization.
Dr. Xingyi Song
Dr. Ye Jiang
Dr. Yunfei Long
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
- natural language processing
- low-resource languages
- NLP applications
- interpretability
- large language model
- sentiment analysis
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