Simplifying Persian NLP for Modern Applications
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Updated
Dec 18, 2025 - Python
Simplifying Persian NLP for Modern Applications
Keyphrase Extraction Review
RAKE - Rapid Automatic Keyword Extraction
Tracking European media sentiment (2025) about international relationship (Pilot : Thailand) and other topics. Production-grade platform featured AI-powered sentiment analysis, semantic search, interactive mind maps, and multilingual EN/DE/TH support. Built with React, FastAPI, PostgreSQL (pgvector), and Google Gemini.
GUI for the great keybert repository.
A keyphrase extractor for Persian
Efficient string matching with regular expressions
Minimal keyword extraction with BERT
Library for reading, editing, and writing LS-DYNA keywords.
An AI-powered web application that analyzes your resume, summarizes your experience, and generates personalized cover letters - all in one place. Built with 💡 LangChain, 🤖 Hugging Face Transformers, and 🌐 Streamlit.
JPCC-RANDOM-PICKER:とにかく早く結果がほしい人向け。JPCCから高速ランダムサンプリングでキーワード抽出。統計的に十分な精度で大幅高速化。普通の用途なら、まずはこれを試してみてください。
JPCC-PICKER:研究者・完璧主義な人向け。学術研究向けなど、JPCCからキーワード抽出を完璧にするための対応。表記ゆれ対応、100%の取りこぼし防止。絶対に見落としがあってはいけない研究や調査に。
JPCC-RAPID-PICKER:時間がかかってもしっかり調べたい人向け。JPCCからキーワード抽出する標準版。バイト正規表現による最適化で全データスキャン。より多くのデータが必要な時や、取りこぼしが心配な時に。
A Python tool to extract key skills and terms from job descriptions, optimizing resumes and LinkedIn profiles for ATS and recruiters.
This project extracts keywords from PDF documents using KeyBERT, maps them to Wikidata entities, and allows you to query the full property relations of each entity through a Streamlit interface.
The method extracts representative keywords for each document in a collection using comparative analysis
SPARClink: Visualizing the Impact of SPARC
AI-generates (OpenAI) GitHub repo topics for you!
RaKUn 2.0 - A fast keyword detection algorithm
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