A Deep Learning-based Traffic Event Detection From Social Media

Jonnalagadda, Jahnavi; Hashemi, Mahdi

doi:10.1109/iri51335.2021.00007

Cited by 4 publications

(1 citation statement)

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“…e essence of a deep learning application is to extract and classify data features. Its research directions are mainly divided into two categories: one is to optimize the way of extracting features from data, and the quality of feature extraction directly a ects the nal classi cation results; the other is to build a good classi er based on the existing feature extraction methods [6].…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning-Based Framework for Social Data Sensing and Fusion for Enterprise Management

Wang

2022

Mathematical Problems in Engineering

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How to effectively realize the perception and fusion of data in the enterprise management society is the core problem that must be solved by enterprise management. On the basis of defining the resource system of enterprise management society, a semantic-oriented metadata model is proposed, combined with the classification of user needs, to build a data fusion framework for enterprise management society based on multisource data. The study designs a multilayer convolutional neural network model to process the data and proposes a recommendation path for the implementation of user data services for the enterprise management society based on the data operation center of the enterprise management society. Finally, it proposes suggestions for the development of the data fusion of the enterprise management society by improving the data fusion standard of the enterprise management society from multiple sources, actively formulating the data opening policy, and exploring the personal data collection and storage protection scheme. Experiments show that the scheme designed in this study is 5% more accurate than the state-of-the-art scheme.

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Section: Introductionmentioning

confidence: 99%