The task of Named Entity Recognition (NER) is an important component of information extraction tasks. Currently, span-based approaches are receiving widespread research attention. Despite their success in many aspects, these approaches also suffer ...

Multivariate time series classification (MTSC) has attracted significant research attention due to its diverse real-world applications. Recently, exploiting transformers for MTSC has achieved state-of-the-art performance. However, existing methods focus ...

The emergence of social media as one of the main platforms for people to access news has enabled the wide dissemination of fake news, having serious impacts on society. Thus, it is really important to identify fake news with high confidence in a timely ...

In this article, we study the problem of personalized news headline generation, which aims to produce not only concise and fact-consistent titles for news articles but also decorate these titles as personalized irresistible reading invitations by ...

Kidney cancer is one of the most common cancers. Precise delineation and localization of the lesion area play a crucial role in the diagnosis and treatment of kidney cancer. Deep learning-based automatic medical image segmentation can help to ...

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Biomedical relation extraction (RE) is the task of automatically identifying and characterizing relations between biomedical concepts from free text. RE is a central task in biomedical natural language processing (NLP) research and plays a ...

Nonintrusive load regulation capacity monitoring is an effective way to obtain load data and achieve load sensing and demand response at low cost, with the identification method for load regulation capacity as its important core technology. A new ...

Traditional sequence recurrent neural networks (SRNNs) have the defect of long time dependence in the prediction of time series, resulting in their poor generalization ability. Moreover, it is required to traverse the whole training ...

• A variational eligibility trace meta-reinforcement recurrent network (VETMRRN) is proposed.

Periodicity or repetition detection has a wide varieties of use cases in human activity tracking, music pattern discovery, physiological signal monitoring and more. While there exists a broad range of research, often the most practical approaches ...

Understanding customer behavior is necessary to develop efficient marketing strategies or launch tailored programs with social value for the public. Customer segmentation is a critical task for understanding diverse and dynamic customer behavior. ...

In the process of training convolutional neural networks, the training data is often insufficient to obtain ideal performance and encounters the overfitting problem. To address this issue, traditional data augmentation (DA) techniques, which are ...

Since traditional intelligent algorithms composed of air quality prediction are commonly used, but such algorithms still have shortcomings for the validity of data, especially the problem of time-series prediction data. In order to investigate the ...

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• The large number of false positives predicted by the existing approaches are filtered.

The study aims at developing a neural network model to improve the performance of Human Phenotype Ontology (HPO) concept recognition tools. We used the terms, definitions, and comments about the phenotypic concepts in the HPO database ...

Without converting the second‐order memristive neural networks (SMNNs) into the usual first‐order systems, this article works on the non‐fragile state estimation of SMNNs with unbounded time‐varying delays. The memristor is treated as uncertainty ...

Purpose. Radiotherapy (RT) is one of the major cancer treatments. However, the responses to RT vary among individual patients, partly due to the differences of the status of gene expression and mutation in tumors of patients. Identification of patients ...

Many recent studies have demonstrated that the propagation patterns of news on social media can facilitate the detection of fake news. Most of these studies rely on the complete propagation networks to build their model, which is not fully ...

• The propagation pattern of news on social media can facilitate fake news detection.
• Propagation2Vec emphasises informative nodes/cascades to detect fake news.
• Propagation2Vec early reconstructs complete propagation networks by ...

Customer churn is the event when customers using the products or services of an organization decide to no longer do so by either switching to another organization or by stopping using those products/services. It takes much more effort to attract ...

Device-to-device (D2D) links scheduling for avoiding excessive interference is critical to the success of wireless D2D communications. Most of the traditional scheduling schemes only consider the maximum throughput or fairness of the system and do not ...

With the rapid development of DNA high-throughput testing technology, there is a high correlation between DNA sequence variation and human diseases, and detecting whether there is variation in DNA sequence has become a hot research topic at present. DNA ...

Distributed drives increase the flexibility of electric vehicles, but puts forward higher requirements on the size and dynamic performance of the motor. An axial flux near-wheel motor suitable for distributed driving is proposed, which adopts a double-...