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genpark-locality-sensitive-hashing-lsh-cosine-index-skill

Random hyperplane Locality-Sensitive Hashing (LSH) for sub-linear cosine similarity candidate generation

Details

External ID
1395119168
Source
GITHUB
Company
—
Product
genpark-locality-sensitive-hashing-lsh-cosine-index-skill
Website domain
github.com
Launched
Sept. 29, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.05976172175249808
Tags
agent-skills, ann-search, cosine-similarity, developer-tools, hashing, hyperplane-hashing, locality-sensitive-hashing, lsh-cosine, mcp, python-standard-library, vector-retrieval
Fetched at
Oct. 1, 2026, 1:02 a.m.
Updated at
Oct. 1, 2026, 1:02 a.m.

Enrichment

Theme
low-level systems and developer tools
Vertical
Horizontal
Function
Search & retrieval
Audience
Developer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
locality-sensitive hashing index for nearest-neighbor candidate generation
Manually corrected
False

Could you build this?

Yes Random hyperplane Locality-Sensitive Hashing (LSH) for cosine similarity is a standard, mathematically straightforward nearest-neighbor algorithm that can easily be generated via vibe coding.

Competitors

Other products that read as similar to this one — 1100 launches clear the similarity bar, closest 8 shown.

Attention rank: #915 of 1101 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 333 days after the earliest competitor.

Other launches for this product