Word Frequency

Inspiration
"I noticed that people often overlook frequently encountered words in their daily reading. By quantifying these patterns, we can transform passive exposure into targeted vocabulary improvement—like a 'Spotify Wrapped' for words."

What It Does
*"A web app that analyzes uploaded texts (notes, articles, emails) to rank words by frequency. Users get:

Interactive word clouds (Top 50 terms)

How We Built It Frontend:

React + Vite (TypeScript) for fast, type-safe UI

Tailwind CSS for responsive design

Backend: 后端 ：

Node.js API with text processing endpoints

Key Libraries: 关键库 ： natural for tokenization/stemming (e.g., "running" → "run")

stopword to filter out common words

Challenges We Ran Into Real-Time Processing: Large files froze the UI → solved with Web Workers for background processing.

TypeScript Typing: Complex word data structures required custom interfaces (e.g., `WordFrequencWordFrequency[]).

Accomplishments We’re Proud Of Achieved <1s response time for 10k-word texts by optimizing React memoization.

Built a zero-dependency analysis algorithm (pure TypeScript).

100% client-side execution option (privacy-first).

What We Learned 我们学到了什么 TS > JS: TypeScript caught 90% of runtime errors during development.

Vite’s Edge: Instant hot-reload for iterative UI tweaks.

Built With

• html5
• tailwindcss
• ts