html-distance — screenshot of github.com

html-distance

This is a Go library for computing HTML page proximity using Charikar's simhash for similarity fingerprinting. It leverages a BK Tree to efficiently find pages within a defined proximity.

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Questions & Answers

What is html-distance?
html-distance is a Go library designed to compute the proximity of HTML pages. It uses Charikar's simhash algorithm to generate similarity fingerprints for web pages.
Who would use the html-distance library?
This library is intended for developers and systems that need to identify near-duplicate HTML content, such as web crawlers, content management systems, or plagiarism detection tools.
How does html-distance determine HTML page similarity?
It determines similarity by computing Charikar's simhash fingerprint for each HTML page. The similarity is then derived from the Hamming distance between these 64-bit fingerprints, with a similarity of greater than 95% indicating potential duplication.
When should I use html-distance?
You should use html-distance when you need to efficiently identify highly similar or duplicated HTML pages within a large dataset, particularly if you require a robust, fingerprint-based comparison.
What is a BK Tree and how is it used in html-distance?
A BK Tree (Burkhard and Keller) is a metric tree data structure used in html-distance to efficiently search for fingerprints that are within a specified proximity distance to a given query fingerprint, leveraging the Hamming distance metric.