Big Data and Cognitive Computing journal is pleased to introduce a new Special Issue entitled Machine Learning in Data Mining for Knowledge Discovery. As the volume of data continues to grow exponentially, there is a need for innovative approaches to data mining that can extract valuable knowledge from unstructured and messy datasets.
The Special Issue aims to explore how machine learning can be applied to different stages of data processing to uncover meaningful patterns, rules, and insights. One of the key challenges in this field is to ensure that the results produced by machine learning algorithms are not only accurate but also interpretable by humans. This can facilitate the application of these insights in practical scenarios where manual intervention is required.
Researchers are encouraged to submit original research articles and reviews that address various aspects of machine learning in data mining. Topics of interest include but are not limited to big data, multi-task learning, cognitive services, and the integration of symbolic and non-symbolic approaches in knowledge discovery.
Manuscripts can be submitted online through the journal’s website, and all submissions will undergo a rigorous peer-review process. Accepted papers will be published continuously in the journal and will be featured on the special issue website. Authors are reminded that submitted manuscripts should not have been published elsewhere and should adhere to the journal’s formatting guidelines.
In conclusion, this Special Issue offers a platform for researchers to showcase their innovative work in the field of machine learning and data mining. By addressing the challenges of the Big Data era and exploring novel approaches to knowledge discovery, this issue aims to advance the field and promote collaboration among researchers worldwide.
