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NLP emotion detector
| Category |
|---|
| Open source |
What is it?
Natural Language Understanding is a collection of APIs that offer text analysis through natural language processing. This set of APIs can analyze text to help you understand its concepts, entities, keywords, sentiment, and more. Additionally, you can create a custom model for some APIs to get specific results that are tailored to your domain. This system is for demonstration purposes only and is not intended to process Personal Data.
The purpose of this project was to create a demonstration of different NLP processes and it was divided into two phases:
- Algorithm development
- Development of a web application
Algorithm development
This phase will cover the creation and testing of different NLP approaches.
NLP approaches that we would like to cover include:
- Emotion detection
- Entity detection (extracting dates, addresses, personal names)
Some of these approaches will require finding and exploring data, data preprocessing, model training, and similar.
Some NLP approaches have already been developed. These should be included in the web application only:
- Sentiment analysis
- Text categorization based on GCP categories
- Keyword extraction
This stage should last 1.5 to 2 months and includes:
- Finding data sets
- Exploratory data analysis
- Exploring and testing different approaches. Reporting results.
- Creating methods for inference
Note: Limited to English language only.
Web application
The web application consists of two parts:
- Application page for algorithm demonstration
- Dashboard for model retraining
Algorithm demonstration
You can find some inspiration regarding the application page for algorithm demonstration here:
https://natural-language-understanding-demo.ng.bluemix.net
https://www.ibm.com/demos/live/natural-language-understanding/self-service/home
The dashboard for model retraining should contain a page for data relabeling for different use cases (e.g. relabeling for sentiment, relabeling for emotion) as well as the relabeling trigger button.
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