Edubuk-U2U

Overview: Edubuk is building an AI-driven CV-to-JD Matching dApp on the blockchain, integrating U2U to revolutionize the hiring process by ensuring tamper-proof verification and AI-powered precision in talent matching. This dApp will leverage blockchain for credential verification (full CV, each credential being verified: TruCV) and AI for intelligent job matching (TruJobs), creating a seamless and trust-driven hiring ecosystem for universities, students, and employers.

Problem Statement: Recruiters face a growing challenge of fake credentials, inefficient hiring processes, and misalignment between candidates’ skills and job descriptions. Traditional job-matching systems rely on self-reported data, making validation time-consuming and unreliable. Moreover, students struggle to get visibility for relevant jobs that align with their verified skills and credentials.

Solution: Edubuk’s AI-driven CV-to-JD Matching dApp on the blockchain provides:

1. Blockchain-Based Credential Verification – CVs, certificates, and academic records are e-sealed and timestamped on the blockchain using Educhain, ensuring authenticity and eliminating fraud.

2. AI-Powered Job Matching – The dApp leverages NLP & Deep Learning algorithms to match verified student profiles with job descriptions based on skills, education, and experience.

   Impact & Traction:

   • 20+ University Partnerships in India, enabling seamless adoption across their student base.

   • Access to 10 Million+ Students, creating one of the largest verified talent pools for employers.

   • Reducing Hiring Fraud – Blockchain-backed verification removes fake degrees and misrepresented resumes.

   Faster Hiring Cycles – AI-driven CV-to-JD matching optimizes hiring efficiency, cutting down recruitment time.
   
   Tech Stack:

   • Blockchain: U2U for credential verification (CV on Chain)

   • AI/ML: NLP models, Deep Learning for JD-CV matching

   • Smart Contracts: Solidity-based contract execution

   • Frontend: React, TypeScript, Tailwind CSS

   • Backend: Node.js, Express.js, MongoDB, Flask (for AI APIs)

   • Smart Contracts: Solidity, Remix IDE, ethers.js

   • Network: U2U Test Network

   • AI & NLP: SentenceTransformer, PyTorch

   • Machine Learning: Cosine Similarity for text matching

   • Data Processing: Pandas for CSV export

   • Decentralized Storage: IPFS

   • Authentication & Security: JWT, OAuth, crypto libraries

   Web3 Integration: Decentralized storage for CVs and credentials
   
   How It Works

   1. Reading Input Files (Preprocessing – NLP)

      • Takes a folder of resumes (CVs/) and a job description file (jd.txt).

      • Extracts text from PDF and TXT files using PyMuPDF (fitz).

   2. Cleaning & Processing Text

      • Removes special characters, punctuation, and extra spaces.

      • Converts text to lowercase for uniformity.

   3. Converting Text into Numerical Representation

      • Uses SentenceTransformer (all-MiniLM-L6-v2) to generate numerical embeddings.

      • Embeddings capture the semantic meaning of sentences.

   4. Matching Resumes with JD

      • Computes cosine similarity between resume and job description embeddings.

      • Calculates a base similarity score.

   5. Skill-Based Weighting

      • Supports Must-Have, Good-to-Have, and Bonus Skills with custom weights.

      • Computes a weighted score based on skill similarity.

   6. Ranking & Output

      • Resumes are sorted by their weighted matching percentage.

      • Generates a results.csv file with resumes and their similarity scores.

   Result: A far more accurate and meaningful resume-job matching, beyond simple keyword checks.

   Why This dApp is a Game Changer?

   1. First-of-its-kind integration of AI job-matching + blockchain verification in university hiring.

   2. Scalable adoption across universities, recruiters, and students with blockchain-based trust.

   3. Decentralized, Transparent, and Efficient Hiring using Educhain, empowering both students and employers.

      This AI-driven CV-to-JD Matching dApp will redefine the future of hiring, making blockchain-backed job recruitment the new standard for universities and employers worldwide.

TruCv – CV Creation

• Fill a simple form with academic credential details.

• Upload certificates for verification.

• Issuer verifies credentials via email.

• A verified CV is created and stored on the blockchain.

• Certificates are stored as NFTs for permanent validation.

Admin Panel

• Verify and approve companies.

• Approve or reject HR accounts.

TruJobs – HR Portal

• HR can post jobs after admin approval.

• Fetch the most relevant CVs/Resumes based on JD using AI-driven matching.

• View and analyze resumes, including blockchain-verified documents.

• Quickly check valid credentials in the Analyze section.

• Schedule interviews with one-click scheduling.

TruJobs – Jobs Portal

• Users do not need to upload a CV.

• System automatically fetches the blockchain-verified resume.

• User can apply directly from the job listing.
  
  Edubuk’s smart contract is deployed on the U2U Test Network, following the official U2U documentation for network configuration.

  Steps to Deploy Smart Contract

  1. Remix IDE

     • Open Remix.

     • Paste the Solidity smart contract code.

     • Compile and deploy using Injected Web3 environment.

  2. MetaMask Configuration

     • Add a Custom RPC Network in MetaMask using U2U testnet details:

       • Network Name: U2U Test Network

       • RPC URL: from U2U docs

       • Chain ID: from U2U docs

       • Currency Symbol: U2U

     • Save and switch to the U2U Test Network.

  3. Faucet

     • Claim test U2U tokens from the U2U Faucet.

     • Deposit these tokens to your MetaMask wallet to cover deployment gas fees.

  4. Contract Deployment

     • In Remix, select Injected Web3 with MetaMask connected to the U2U Test Network.

     • Deploy the contract and note the contract address.

  The contract is now live and ready for integration with the Edubuk platform.