RRepoGEO

REPOGEO REPORT · LITE

ZJULearning/nsg

Default branch master · commit 5ec8fadf · scanned 6/4/2026, 8:49:51 AM

GitHub: 733 stars · 166 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface ZJULearning/nsg, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add explicit topics for Approximate Nearest Neighbor Search

    Why:

    COPY-PASTE FIX
    approximate-nearest-neighbor-search, anns, graph-based-search, similarity-search, vector-search, high-performance-computing
  • highreadme#2
    Add a concise disambiguation statement immediately after the H1

    Why:

    COPY-PASTE FIX
    This repository provides the official implementation of NSG, a graph-based Approximate Nearest Neighbor Search (ANNS) algorithm, not a Neural Scene Graph.
  • mediumhomepage#3
    Add a homepage link to the associated PVLDB paper or project page

    Why:

    COPY-PASTE FIX
    [Link to PVLDB paper or project page for "Fast Approximate Nearest Neighbor Search With The Navigating Spread-out Graphs"]

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface ZJULearning/nsg
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
facebookresearch/faiss
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. facebookresearch/faiss · recommended 2×
  2. spotify/annoy · recommended 2×
  3. nmslib/hnswlib · recommended 1×
  4. ScaNN · recommended 1×
  5. milvus-io/milvus · recommended 1×
  • CATEGORY QUERY
    How to implement fast approximate nearest neighbor search for large-scale data?
    you: not recommended
    AI recommended (in order):
    1. Faiss (facebookresearch/faiss)
    2. Hnswlib (nmslib/hnswlib)
    3. Annoy (spotify/annoy)
    4. ScaNN
    5. Milvus (milvus-io/milvus)
    6. Weaviate (weaviate/weaviate)
    7. Elasticsearch (elastic/elasticsearch)

    AI recommended 7 alternatives but never named ZJULearning/nsg. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are efficient graph-based algorithms for high-performance nearest neighbor retrieval?
    you: not recommended
    AI recommended (in order):
    1. HNSW (Hierarchical Navigable Small World)
    2. ANNOY (Approximate Nearest Neighbors Oh Yeah) (spotify/annoy)
    3. Faiss (Facebook AI Similarity Search) (facebookresearch/faiss)
    4. ScaNN (Scalable Nearest Neighbors) (google-research/google-research)
    5. DiskANN
    6. NMSLIB (Non-Metric Space Library) (nmslib/nmslib)

    AI recommended 6 alternatives but never named ZJULearning/nsg. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of ZJULearning/nsg?
    pass
    AI named ZJULearning/nsg explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts ZJULearning/nsg in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ZJULearning/nsg explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo ZJULearning/nsg solve, and who is the primary audience?
    pass
    AI named ZJULearning/nsg explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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ZJULearning/nsg — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite