AIMC Topic: Data Mining

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Construction and Model Realization of Financial Intelligence System Based on Multisource Information Feature Mining.

Computational intelligence and neuroscience
Multisource information mining systems and related business intelligence technology are currently a hot topic of research. However, the current commercial applications and applications are not ideal in terms of application. Because there is still muc...

Analysis of Data Interaction Process Based on Data Mining and Neural Network Topology Visualization.

Computational intelligence and neuroscience
This paper addresses data mining and neural network model construction and analysis to design a data interaction process model based on data mining and topology visualization. This paper performs preprocessing data operations such as data filtering a...

A Neural Network Model for Digitizing Enterprise Carbon Assets Based on Multimodal Knowledge Mapping.

Computational intelligence and neuroscience
In this paper, a multimodal knowledge mapping approach is used to digitize enterprise carbon assets, and a corresponding neural network model is designed for use in the practical process. Rich textual entity labels associated with images are obtained...

Research on Embedded Multifunctional Data Mining Technology Based on Granular Computing.

Computational intelligence and neuroscience
Due to the influence and limitations of the multisourced, heterogeneous, and unbalanced characteristics of embedded multifunctional data, the application effect of the current data mining technology is not good, and the accuracy is low. To solve the ...

Systems Drug Discovery for Diffuse Large B Cell Lymphoma Based on Pathogenic Molecular Mechanism via Big Data Mining and Deep Learning Method.

International journal of molecular sciences
Diffuse large B cell lymphoma (DLBCL) is an aggressive heterogeneous disease. The most common subtypes of DLBCL include germinal center b-cell (GCB) type and activated b-cell (ABC) type. To learn more about the pathogenesis of two DLBCL subtypes (i.e...

Deep Learning Versus Traditional Solutions for Group Trajectory Outliers.

IEEE transactions on cybernetics
This article introduces a new model to identify a group of trajectory outliers from a large trajectory database and proposes several algorithms. These can be split into three categories: 1) algorithms based on data mining and knowledge discovery, whi...

FLeAC: A Human-Centered Associative Classifier Using the Validity Concept.

IEEE transactions on cybernetics
Fuzzy associative classifiers (FACs) have recently received considerable attention in the data mining community due to their ability to address the imprecision and graduality of truth. Similar to their more traditional statistical peers, these classi...

A Complete Process of Text Classification System Using State-of-the-Art NLP Models.

Computational intelligence and neuroscience
With the rapid advancement of information technology, online information has been exponentially growing day by day, especially in the form of text documents such as news events, company reports, reviews on products, stocks-related reports, medical re...

Analysis of Human Exercise Health Monitoring Data of Smart Bracelet Based on Machine Learning.

Computational intelligence and neuroscience
The smart bracelet has become a hot-selling commodity, according to a daily consumption survey. Based on people's interest and concern for their health, the smart bracelet, as a design and application for achieving healthy weight loss monitoring, is ...

Deep Graph Learning for Anomalous Citation Detection.

IEEE transactions on neural networks and learning systems
Anomaly detection is one of the most active research areas in various critical domains, such as healthcare, fintech, and public security. However, little attention has been paid to scholarly data, that is, anomaly detection in a citation network. Cit...