AIMC Topic: Data Mining

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Prediction and Big Data Impact Analysis of Telecom Churn by Backpropagation Neural Network Algorithm from the Perspective of Business Model.

Big data
This study aims to transform the existing telecom operators from traditional Internet operators to digital-driven services, and improve the overall competitiveness of telecom enterprises. Data mining is applied to telecom user classification to proce...

Data-Driven Low-Frequency Oscillation Event Detection Strategy for Railway Electrification Networks.

Sensors (Basel, Switzerland)
Low-frequency oscillations (LFO) occur in railway electrification systems due to the incorporation of new trains with switching converters. As a result, the increased harmonic content can cause catenary stability problems under certain conditions. Mo...

A System for Converting and Recovering Texts Managed as Structured Information.

Scientific reports
This paper introduces a system that incorporates several strategies based on scientific models of how the brain records and recovers memories. Methodologically, an incremental prototyping approach has been applied to develop a satisfactory architectu...

Feature Selection and Dwarf Mongoose Optimization Enabled Deep Learning for Heart Disease Detection.

Computational intelligence and neuroscience
Heart disease causes major death across the entire globe. Hence, heart disease prediction is a vital part of medical data analysis. Recently, various data mining and machine learning practices have been utilized to detect heart disease. However, thes...

Human monkeypox diagnose (HMD) strategy based on data mining and artificial intelligence techniques.

Computers in biology and medicine
In May 2022, monkeypox re-emerged as a rare zoonotic disease that is an important viral disease for public health. Monkeypox can be transmitted from animals to humans, between humans through close contact with an infected human, or with a virus stain...

The New Version of the ANDDigest Tool with Improved AI-Based Short Names Recognition.

International journal of molecular sciences
The body of scientific literature continues to grow annually. Over 1.5 million abstracts of biomedical publications were added to the PubMed database in 2021. Therefore, developing cognitive systems that provide a specialized search for information i...

An imConvNet-based deep learning model for Chinese medical named entity recognition.

BMC medical informatics and decision making
BACKGROUND: With the development of current medical technology, information management becomes perfect in the medical field. Medical big data analysis is based on a large amount of medical and health data stored in the electronic medical system, such...

Continual learning with attentive recurrent neural networks for temporal data classification.

Neural networks : the official journal of the International Neural Network Society
Continual learning is an emerging research branch of deep learning, which aims to learn a model for a series of tasks continually without forgetting knowledge obtained from previous tasks. Despite receiving a lot of attention in the research communit...

Development of benchmark datasets for text mining and sentiment analysis to accelerate regulatory literature review.

Regulatory toxicology and pharmacology : RTP
In the field of regulatory science, reviewing literature is an essential and important step, which most of the time is conducted by manually reading hundreds of articles. Although this process is highly time-consuming and labor-intensive, most output...

Biomedical named entity recognition with the combined feature attention and fully-shared multi-task learning.

BMC bioinformatics
BACKGROUND: Biomedical named entity recognition (BioNER) is a basic and important task for biomedical text mining with the purpose of automatically recognizing and classifying biomedical entities. The performance of BioNER systems directly impacts do...