X Deng, Y Li, J Weng, J Zhang - Multimedia Tools and Applications, 2019 - Springer
Big multimedia data is heterogeneous in essence, that is, the data may be a mixture of video, audio, text, and images. This is due to the prevalence of novel applications in recent …
Dealing with imbalanced data is a prevalent problem while performing classification on the datasets. Many times, this problem contributes to bias while making decisions or …
P Craja, A Kim, S Lessmann - Decision Support Systems, 2020 - Elsevier
Financial statement fraud is an area of significant consternation for potential investors, auditing companies, and state regulators. The paper proposes an approach for detecting …
J Hartmann, J Huppertz, C Schamp… - International Journal of …, 2019 - Elsevier
Online social media drive the growth of unstructured text data. Many marketing applications require structuring this data at scales non-accessible to human coding, eg, to detect …
This paper provides a review and commentary on the past, present, and future of numerical optimization algorithms in the context of machine learning applications. Through case …
The extraction of useful insights from text with various types of statistical algorithms is referred to as text mining, text analytics, or machine learning from text. The choice of …
In this paper, we document basic facts regarding public debates about controversial political issues on Chinese social media. Our documentation is based on a dataset of 13.2 billion …
With the utilization of deep learning approaches, the key factors for a successful application are sufficient datasets with reliable ground truth, which are generally not easy to obtain …
The problem of classification has been widely studied in the data mining, machine learning, database, and information retrieval communities with applications in a number of diverse …