PageRank Search Engine
A working search engine built around a from-scratch PageRank implementation, run on a real corpus to rank pages by both link authority and query relevance.
8★
on GitHub
from scratch
power iteration
The problem
Search engines rank pages by relevance and authority. I wanted to implement the authority half, PageRank, from scratch, and run it on a real web-link graph rather than a toy example.
Approach
- 1.Built the web-link graph from the Lawfare national-security blog corpus.
- 2.Implemented PageRank via power iteration in NumPy; the linear algebra is mine, not a library's.
- 3.Combined link-authority scores with query relevance to rank results.
Result
A working search engine that ranks real pages by query relevance. 8 stars on GitHub.
Stack
PythonNumPyLinear AlgebraInformation Retrieval