Mining valuable hidden knowledge from large-scale data relies on the support of reasoning
technology. Knowledge graphs, as a new type of knowledge representation, have gained …

A sentiment analysis has received a lot of attention from researchers working in the fields of
natural language processing and text mining. However, there is a lack of annotated data …

Deep neural network models have achieved remarkable results in sentiment classification.
Traditional feature-based methods perform slightly worse than deep learning methods in …

Deep neural networks (DNN) have achieved remarkable results in sentiment classification.
Some ensemble methods of DNN models and traditional feature-based models are …

Financial fraud detection has gained constant attention from researchers, practitioners, and
regulators. Because of its concealment and ease of manipulation, related-party transactions …

Cross-language plagiarism detection aims to detect plagiarised fragments of text among
documents in different languages. In this paper, we perform a systematic examination of …

Training (source) domain bias affects state-of-the-art object detectors, such as Faster R-
CNN, when applied to new (target) domains. To alleviate this problem, researchers …

In this paper we show how a vector-based word representation obtained via word2vec can
help to improve the results of a document classifier based on bags of words. Both models …

In the field of natural language processing and text mining, sentiment analysis (SA) has
received huge attention from various researchers' across the globe. By the prevalence of …

Generally, QA systems suffer from the structural difference where a question is composed of
unstructured data, while its answer is made up of structured data in a Knowledge Graph …