zeeshanlakhani/proof_docsimilarity — explained in plain English
Analysis updated 2026-08-15 · repo last pushed 2011-03-09
Learn how document similarity works by running the code with two text passages and seeing the resulting score.
Study the math behind converting text into vector representations and comparing them.
Use the included PDF as a reference for understanding the linear algebra concepts behind text comparison.
| zeeshanlakhani/proof_docsimilarity | aonez/macreflower | burningtyger/gmail-notifr | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | Objective-C | Objective-C | Objective-C |
| Last pushed | 2011-03-09 | 2016-11-27 | 2013-01-22 |
| Maintenance | Dormant | Dormant | Dormant |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 1/5 | 2/5 | 2/5 |
| Audience | researcher | general | general |
Figures from each repo's GitHub metadata at analysis time.
Requires MATLAB to run the similarity function, which may not be readily available to all users.
This project is a proof-of-concept tool that figures out how similar two pieces of text are to each other. It was built as a class assignment for a math course at NYU, and it lets you feed it two documents or text passages to get back a measure of how closely they relate. Under the hood, it works by turning text into numbers and then comparing those numbers using basic linear algebra. The approach ignores "stop words", common words like "the" or "and" that don't carry much meaning, and focuses on the more significant words in each document. By converting the remaining words into a mathematical representation, the tool can calculate how much the two documents overlap in content. The main use case is academic: someone learning about document similarity models, vector spaces, or the math behind text comparison. You would run it in MATLAB by calling a function with two text inputs, and it returns a similarity score. The README notes that a PDF with more detail about the problem is included in the repository. It's worth noting that this is a straightforward academic exercise rather than a production-ready library. The author even apologizes in advance for potentially messy code, so it's best treated as a learning reference rather than something to build on directly.
A proof-of-concept tool that measures how similar two pieces of text are by turning words into numbers and comparing them with basic linear algebra. Built as an NYU math class assignment.
Mainly Objective-C. The stack also includes MATLAB, Objective-C.
Dormant — no commits in 2+ years (last push 2011-03-09).
No license information is provided, so default copyright restrictions apply and you should contact the author before reusing this code.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Don't trust strangers blindly. Verify against the repo.