Identifying Relevant Text from Text Document Using Deep Learning
| Autor: | P Parvathi, T S Jyothis |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer science
business.industry Deep learning Text document computer.software_genre Convolutional neural network Test (assessment) Task (project management) ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Artificial intelligence business F1 score Value (mathematics) computer Natural language processing |
| Zdroj: | 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET). |
| DOI: | 10.1109/iccsdet.2018.8821192 |
| Popis: | Now-a-days the amount of information available on the web is enormous and incrementing at an exponential rate. Thus identifying relevant text from text document has become very crucial. Text classification is the task of relegating a document under a predefined category. There are several methods to identify which words in text documents are important to explain the category it is associated with. The proposed approach uses convolution neural network with deep learning. And the deep learning is used to predict the categories accurately. Thus by calculating the test’s accuracy by F1 Score, we get an accuracy value which is approximately equal to 1. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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