The data mining and machine learning landscape have evolved significantly in recent years, driven by the rise of big data and the emergence of complex models. Researchers from the Ministry of Education Key Laboratory of Knowledge Engineering with Big Data at Hefei University of Technology in China are at the forefront, focusing on knowledge graph construction, multimodal fusion, and AutoGL techniques.
In a special issue aimed at exploring the latest trends, challenges, and applications in data mining and machine learning within the context of big knowledge and large models, researchers are invited to contribute original research articles, reviews, and short communications. The goal is to push the boundaries of these fields and uncover novel methodologies, theoretical insights, experimental results, and practical applications.
Manuscripts can be submitted online through the designated website. Submitted papers should not have been published previously or be under consideration elsewhere. The journal, Mathematics, is an international peer-reviewed open-access publication from MDPI. Accepted papers will be published continuously and listed on the special issue website.
Authors are encouraged to adhere to the submission guidelines, ensuring that manuscripts are well-formatted, use good English, and align with the focus keywords of data mining and machine learning. The Article Processing Charge (APC) for publication is 2600 CHF (Swiss Francs), with the option for authors to utilize MDPI’s English editing service.
The evolving landscape of data mining and machine learning presents both challenges and opportunities for researchers worldwide. By contributing to this special issue, experts can share their insights and advancements, driving innovation in the era of big knowledge and large models.
