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genpark-node2vec-biased-random-walk-embedding-skill

Node2Vec 2nd-order biased random walk generator with return (p) and in-out (q) hyperparameters

Details

External ID
1392515132
Source
GITHUB
Company
—
Product
genpark-node2vec-biased-random-walk-embedding-skill
Website domain
github.com
Launched
Sept. 28, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.05976172175249808
Tags
agent-skills, feature-extraction, graph-embedding, graph-mining, graph-representation-learning, mcp, network-science, node2vec, python-standard-library, random-walk, skip-gram
Fetched at
Sept. 30, 2026, 1:02 a.m.
Updated at
Sept. 30, 2026, 1:02 a.m.

Enrichment

Theme
low-level systems and developer tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
biased random walk generator for graph embeddings
Manually corrected
False

Could you build this?

Yes Node2Vec biased random walk algorithms (with return p and in-out q parameters) are well-understood textbook graph algorithms that AI coding assistants can generate effortlessly in Python or C++.

Competitors

Other products that read as similar to this one — 578 launches clear the similarity bar, closest 8 shown.

Attention rank: #352 of 579 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 332 days after the earliest competitor.

Other launches for this product

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