White paper of SmartCV is available here: https://drive.google.com/file/d/1IPiCw11GEDM4H4DonKM6hYGk3Zh0YuhC/view?usp=sharing


Each year, there are millions of people seeking jobs, millions of jobs needing employees, billions of US dollars, and huge labor costs being invested for job recruitment. In another aspect, there is a truth that everyone has talent in his/her specific field. Due to lack of information, many people cannot find their most suitable job so that they cannot show their talent in working, which results in unhappy life for employees and low labor productivity for organizations.

The traditional Web2 platforms such as Linkedin, Meetup, etc. have somehow succussed in their job of connecting employees and employers. However, using these platforms users must aware that they may be tradeoff the risks relating to their privacy data (such as user data leakage, illegal selling of user data). More importantly, these Web2 platforms are not smart and decentralized enough to become labor hubs for matching talents. Curriculum Vitae (CV) of laborers are not certified and thus being an unreliable source of information for employers on deciding who will be most suitable for their provided job positions.

Fig.1: Inspiration for SmartCV chain

Inspired by these truths, we develop a Smart CV chain (SCV-chain) as a labor hub for matching talents to the appropriate job positions. SmartCV aims to help organizations find the right talent for their provided job at low cost for recruitment, and employees easily find job positions most suitable for their talents and skills. In such a way, SmartCV aims to contribute to building up a smart and happy society.

What it does

SmartCV allows the following things to happen (Fig. 2):

Fig. 2: SCV-chain Overviews.
  • Individual users (employees) create and manage CVs by themselves, therefore they can get off the risk of privacy issues

  • Organizations can make business by certifying CV/certificate information of individual users

  • Organizations broadcasts job position information to individual users

  • Organizations are recommended a large number of reliable CVs suitable for their provided job so that they can find the right talent at a low cost for recruitment

  • Thanks to the talent matching mechanism of SmartCV, employees can find and apply for job positions most suitable for their talents and skills

How we built it

Fig. 3: Project Platform Overview

Fig. 3 shows the overview of the system. It includes three main parts: SmartCV chain network, Distributed Processing Platform (DPP), and Frontend Web Interface (FWI).

  • SmartCV chain network: This is the main component of the system. It is a decentralized blockchain network that records the reliable CV information of users, as well as the profile of organizations into a blockchain ledger named SmartCV. The platform allows individual users to create their own CVs, allows a CV item to be certified and uploaded, allows organizations to create and broadcast their recruitment job information, and allows individual users to apply for jobs. We develop the SmartCV by using the Substrate platform and Rust programing language. The BABE and GRANPA consensuses are employed to secure the network.

  • Decentralized Processing Platform (DPP): This platform connects the user interface with the SmartCV. The DPP does the following tasks. 1) It collects CV items of users from the SmartCV ledger and builds up a user-friendly CV and/or profile from these items if there is a request to view CV. 2) It runs a Web3-based Community Evaluation Algorithm (Web3CEA) to certify a specific piece of CV information (CV item) of users. 3) It implements a Keyword Search engine and Artificial Intelligent (AI) engine to search for CVs best matched to a job position and job positions best matched to a CV. We develop the DPP by using several programming languages such as JavaScript, ReactJS, Python, NodeJS, etc.

  • Frontend Web Interface (FWI): This is a user-friendly interface so that individuals and organizations can interact with our system. It is developed by using Web programming languages such as HTML, ReactJS, etc.

Challenges we ran into

The most four challenges we have been facing during our development process, and our proposed solutions for the challenges are as follows.

  • Challenges #1: How to provide a reliable source of CVs?

We provide two solutions: First, organizations such as universities, education centers, companies may decide to become certified entities (CEs) of the network. These CEs certify CV items of their belonging to students or employees. Second, we introduce the Web3-based Community Evaluation Algorithm (Web3CEA) to further provide the reliability of data. The Web3CEA performs two tasks: 1) Web3CEA judges the reliable score of CEs by utilizing the historical data related to these CEs. 2) Web3CEA provides a reliable score of new broadcast CV items. To do so, Web3CEA allows organizations and individuals to become validators. Validators provide scores of CV items. And Web3CEA calculates CV reliable score from input data such as score provided by validators, and the relationship between validators and content of CV item. For example, CV item such as “Mr.A has been a student of university B from yyyy to yyyy”. Then, Web3CEA may consider the relationship between validators and university B as input data for computing the reliable score of that CV item.

Fig. 4: Web3CEA for Data Reliability in Trustless Environment
  • Challenges #2: How to broadcast the CVs to organizations but also protect users' privacy?

To address this challenge, we propose a new method named CV Delivery Mechanism (CDM). The CDM appropriately combines symmetric cryptography algorithms such as advanced encryption Standard (AES) and asymmetric cryptography algorithms such as Rivest–Shamir–Adleman (RSA). The CDM allows CVs of users and user privacy data could be encrypted for security purposes. However, some specific users and organizations may be allowed to see these encrypted data without the need of delivering the encrypted key.

  • Challenges #3: How to match talents to a job position?

We provide two stages of talent matching. The first one is the Keyword Search Engine which matches the CVs to the most appropriate job position based on keyword matching. The second is to use an AI engine to further enhance the accuracy of talent matching results.

  • Challenges #4: How to make the system operate smoothly?

We propose an appropriate system operating protocol, a unique data structure, and a list of smart contract functions.

Accomplishments that we're proud of

SmartCV chain won the first prize in OCT Substrate minihackathon. And this project is the upgraded version in which Web3-based Community Evaluation Algorithm (Web3CEA) is introduced to provide data reliability in a trustless environment. The Web3CEA leverages community relationships to corroborate information so that the SmartCV provide a reliable source of truth of CVs. Therefore, the participant of government organizations as the purpose of certifying CV contents is welcomed but not mandatory.

We are proud of our working team in which members are full of enthusiasm, high motivation, and everyone has talent in their specific field. We work enthusiastically and are always full of respect and love towards our colleagues. We work with the mission of creating systems for supporting a smart and happy society. Some of us are good at Frontend development, some are experts on Blockchain backend development, some master blockchain technology in both Dapp development and mining hardware chip design, some have rich experience in machine learning and AI, some have talent as project managers and team leader. Thanks to our experience, enthusiasm, motivation, and love energy, we strongly believe that our project will go succeed as our plan.

We have a clear and high motivated roadmap for our project. We know what we should do next to bring SmartCV to the community and benefit society. We can imagine a bright future for our SmartCV system. It will succeed far beyond the current Web2 platforms such as Linkedin, and Meetup. Success is just a matter of time. And your support helps time to success becomes much shorter.

What we learned

We have learned Blockchain technology in both Dapp development and mining hardware chip design. We have learned the Substrate platform and several programming languages such as Rust, Solidity, Python, JavaScript, ReactJS, etc. We have learned and experienced the beauty of team working spirit.

What's next for Smart CV

The roadmap of our project is shown in Fig. 5.

We have built a basic SmartCV demo on the substrate, and a basic Web interface that allows users to interact with SmartCV. Currently, users can add and view CV items. A simple talent matching using a keyword search engine and Octopus interface is on developing. The Web3CEA algorithm is testing.

2022/8, we plan to launch the SmartCV version 1 as an Octopus appchain. This is an initial completed version with features such as: add & view CV, Web3CEA basic certification, add job position, apply for a job, basic talent matching using Keyword Search engine.

2023/2: We release SmartCV version 2 which enhances the features such as Web3CEA advanced certification by employing AI engine, advanced talent matching with AI engine, the marketing campaign for Initial Coin Offering (ICO).

2023/8: We run the ICO to get funds for further project development.

Fig. 5: Project Roadmap

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