nlp-visualization

用python實現文字雲

Interactive GPT-2 inference explorer with token probability visualization, entropy curves, confidence heatmap, and sampling strategy comparison. Built on nanoGPT.

TASC: Topic-Aware Semantic Change. A web application for visualizing and characterizing lexical semantic change across time with integrated topic modeling and 3D interaction.

An example of the Text Annotation Graphs (TAG) system in action.

This repository contains a sentiment analysis project on Baldur's Gate 3 Steam reviews using natural language processing (NLP) techniques. It leverages machine learning and deep learning models to classify reviews as positive or negative. The project includes preprocessing steps, feature extraction, and performance evaluation across various models.

Aspect-Based Sentiment Explorer (ABSA) is a lightweight static HTML viewer for multi-aspect reviews. It uses a BERT baseline by default, with optional SHAP plots, to display per-aspect sentiment using two-tone aspect/sentiment chips, stacked bars, and a Context toggle highlighting textual evidence. No server required.

See which semantic primitives your answer lights up, live — brain-shaped node graph, EEG-style traces, composition card. 语义脉冲 / HowNet 义原可视化