# AI-Powered Feature for Sentiment Analysis in DenoJS
Create an AI-driven sentiment analysis tool using Natural Language Processing (NLP) techniques to analyze customer reviews and feedback within a DenoJS application. The tool should classify sentiments as positive, negative, or neutral, providing actionable insights for businesses to improve their products and services.
**Functional Requirements:**
* Implement a sentiment analysis model using a pre-trained NLP library (e.g., `@nlpjs/model` or `compromise`) in DenoJS.
* Develop a function to preprocess user input data (text reviews) by tokenizing, removing stop words, and converting text to lowercase.
* Train the model using a dataset of labeled reviews and evaluate its performance using metrics such as accuracy, precision, and recall.
* Integrate the sentiment analysis tool with a DenoJS web application, allowing users to input reviews and receive real-time sentiment analysis results.
**Code Snippet:**
```typescript
import { tokenize } from 'https://deno.land/
[email protected]/tokenize/mod.ts';
import { Nlp } from 'https://deno.land/x/
[email protected]/mod.ts';
const nlp = new Nlp();
// Preprocess user input data
function preprocessText(text: string): string[] {
const tokens = tokenize(text).map((token) => token.text.toLowerCase());
return tokens.filter((token) => !stopWords.includes(token));
}
// Train the sentiment analysis model
async function trainModel(data: { text: string; sentiment: string }[]) {
nlp.addDocument(data);
await nlp.train();
}
// Analyze user input sentiment
async function analyzeSentiment(text: string): Promise<string> {
const preprocessedText = preprocessText(text);
const result = await nlp.process(preprocessedText);
return result.sentiment;
}
// Integrate with DenoJS web application
addEventListener('fetch', (event) => {
event.respondWith(
(async () => {
const userInput = await event.request.json();
const sentiment = await analyzeSentiment(userInput.review);
return new Response(`Sentiment: ${sentiment}`, {
headers: { 'Content-Type': 'text/plain' },
});
})()
);
});
```
**Best Practices:**
* Use DenoJS's built-in support for ES modules to import NLP libraries and utilities.
* Implement caching mechanisms to store preprocessed data and trained models, optimizing performance and reducing computational overhead.
* Ensure the AI tool is scalable and adaptable to handle large volumes of user input data and varying sentiment analysis requirements.
By implementing this AI-powered sentiment analysis feature, businesses can gain valuable insights into customer feedback, enabling data-driven decision-making and improved customer satisfaction.
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