Most social-media platforms support product endorsement by displaying advertisements on behalf of certified sellers. These advertisements lack target-audience knowledge and have limited area of creativity for the sellers. Such generic ads have a low probability of reaching the right audience.
TLDR; there are two main areas in tailored discovery to improve ad success:
- Recommend specifc products to users based on user data
- Allowing seller to choose an influencer for advertisement.
Our tailored discovery system is a two part AI service, where
- Knowledge Graphs helps sellers by endorsing their product in the form of a personalized advertizement, specifically to a users who are more likely to buy their products based on their activity/interactions on Tiktok.
- GenAI helps sellers to choose an influencer whose digital footprints are utilized to generate a personalized ad video, in a controlled manner.
Checkout this schema diagram. Database Name: tiktok-clone
git clone https://github.com/Hemant7499/tiktok-techjam-2024
- Setup an Appwrite account
- rename .env.example to .env
- Fill out credentials from Appwrite
Run the following commands.
npm i npm run dev
Download desktop app for neo4j via this link Setup your neo4j knowledge graph by reading the documentation
- scipy
- ffmpeg
- openai
- soundfile
- liberosa
- torch
- transformers
Credits for base project to John-Weeks-Dev