text-mining-science

Community

Turn research papers into structured insights

Authorxjtulyc
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps you extract actionable knowledge from scientific literature by identifying topics, scientific entities, claims, and emerging trends within research text corpora.

Core Features & Use Cases

  • Topic modeling for scientific corpora: Use LDA or NMF to discover latent themes in abstracts or full-text.
  • Scientific information extraction: Extract named entities such as methods, metrics, datasets, genes/chemicals/diseases (via configurable pattern logic) and pull claim-like sentences from paper text.
  • Trend and keyword analysis: Combine TF-IDF, RAKE-inspired phrase scoring, and temporal comparisons to detect research fronts across years.
  • Similarity and recommendation foundations: Build document-topic representations and keyword vectors that can support literature search and recommendation.

Quick Start

Use the text-mining-science skill on a set of scientific abstracts to produce topic clusters, top keywords, and a timeline of emerging terms.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: text-mining-science
Download link: https://github.com/xjtulyc/awesome-rosetta-skills/archive/main.zip#text-mining-science

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
View Source Repository

Agent Skills Search Helper

Install a tiny helper to your Agent, search and equip skill from 471,000+ vetted skills library on demand.