Inside HumbleWorth's Domain Valuation Engine
HumbleWorth uses artificial intelligence to estimate the value of domain names. The platform uses language models trained on data sets reflecting the domain name market.
AI-Powered Domain Analysis
The AI models use freely available language models to understand linguistic patterns and domain name structures.
The valuations build on work from Microsoft, Eleuther, and Huggingface.
Data Sources
HumbleWorth's valuations use these data sources:
- Dropped Domains: By studying domains that have been let go, we learn about market trends and the lifecycle of domain names.
- Active Website Domains: Examining domains currently in use gives us insight into successful digital real estate's characteristics.
- Domain Marketplaces: We analyze data from domain sales platforms, like Godaddy Auctions, to keep abreast of real-time market dynamics.
- Historical Auction Data: Our models are fine-tuned using a 20-year dataset from DNPric.es, which includes over 3 million domain name auction transactions, providing a long-term perspective on domain valuation.
The Neural Network Model
HumbleWorth's valuation predictions are generated by a neural network that synthesizes domain and linguistic data. Here's a brief overview of the process:
- Embedding Domains: Domains are tokenized and converted into vector form, which encapsulates their linguistic and market attributes.
- Sequential Processing: These vectors are processed through a sequence of neural network layers, each refining the accuracy of the valuation prediction.
- Valuation Range Prediction: The network outputs a range of values, offering a probabilistic estimation that reflects the current market's complexity.
The tool uses AI and market data for domain estimates, available for free.