ResearchPaperScholarlyArticlesRecSystem

Recommender system and search engine for scholarly articles/research papers using Doc2Vec

Generate Convert Improve

Install / Use

/learn @DeviantPadam/ResearchPaperScholarlyArticlesRecSystem

About this skill

Quality Score

0/100

README

recommender_system_research_papers_or_scholarly_articles_doc2vec

Recommender system for Scholarly Articles Dataset available at <link>https://www.kaggle.com/neelshah18/arxivdataset</link> and text file for topics explanation is copied from </link>https://arxiv.org/archive/cs</link>

Source notebook available at <link>https://www.kaggle.com/deviantpadam/scholarly-articles-recommender-system-doc2vec</link>

<hr> Site is live on <link>http://deviantpadam.pythonanywhere.com/</link> <hr> Instructions to run the flask app - <ol> <li> Install git </li> <li> Open cmd/terminal </li> <li> Clone this repository using <code>git clone <link>https://github.com/DeviantPadam/rec_system.git</link></code> or download the zip file. </li> <li> Install required dependencies from <i>requirement.txt</i> using <code>pip install package_name</code> or <code>conda install -c </code> </li> <li> Open cmd/terminal and set current directory to repository directory using <code>cd repository_path</code> </li> <li> Execute <code>export FLASK_APP=recommender.py</code>(linux) or <code>set FLASK_APP=recommender.py </code>(windows) </li> <li> Then execute <code>flask run</code> <li> Click on the development link to see the flask app</li> <ol>

Related Skills

claude-opus-4-5-migration

83.9k

Migrate prompts and code from Claude Sonnet 4.0, Sonnet 4.5, or Opus 4.1 to Opus 4.5

model-usage

339.3k

Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.

TrendRadar

49.9k

⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机，也支持接入 MCP 架构，赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ，数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。

mcp-for-beginners

15.7k

This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.

DeviantPadam

View profile

View on GitHub

GitHub Stars6

CategoryEducation

Updated2y ago

Forks1

DeviantPadam/ResearchPaperScholarlyArticlesRecSystem

Languages

CSS

Security Score

60/100

Audited on Aug 4, 2023

No findings