RRepoGEO

REPOGEO REPORT · LITE

wzhe06/Reco-papers

Default branch master · commit 2c617a16 · scanned 5/9/2026, 3:17:44 PM

GitHub: 3,543 stars · 815 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 wzhe06/Reco-papers, 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
  • highabout#1
    Clarify GitHub description to emphasize "curated collection"

    Why:

    CURRENT
    Classic papers and resources on recommendation
    COPY-PASTE FIX
    A curated collection of classic and modern research papers and learning resources on recommendation systems.
  • mediumtopics#2
    Add more specific topics related to paper collections

    Why:

    CURRENT
    deep-learning, exploration-exploitation, machine-learning, recommendation, recommender-system, reinforcement-learning
    COPY-PASTE FIX
    deep-learning, exploration-exploitation, machine-learning, recommendation, recommender-system, reinforcement-learning, paper-collection, research-papers, academic-resources
  • lowreadme#3
    Add a concise English introductory sentence to the README

    Why:

    COPY-PASTE FIX
    This repository serves as a dynamically updated, curated collection of classic and modern research papers, learning materials, and industry insights related to recommendation systems.

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 wzhe06/Reco-papers
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ACM RecSys Proceedings
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ACM RecSys Proceedings · recommended 1×
  2. ACM Digital Library · recommended 1×
  3. arXiv.org · recommended 1×
  4. Google Scholar · recommended 1×
  5. Foundations and Trends® in Machine Learning · recommended 1×
  • CATEGORY QUERY
    Where can I find academic papers and learning materials on modern recommender systems?
    you: not recommended
    AI recommended (in order):
    1. ACM RecSys Proceedings
    2. ACM Digital Library
    3. arXiv.org
    4. Google Scholar
    5. Foundations and Trends® in Machine Learning
    6. Coursera
    7. edX
    8. Recommender Systems Specialization
    9. Recommender Systems: The Textbook
    10. Deep Learning for Recommender Systems

    AI recommended 10 alternatives but never named wzhe06/Reco-papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are essential deep learning research papers for building personalized recommendation engines?
    you: not recommended
    AI recommended (in order):
    1. Neural Collaborative Filtering (NCF)
    2. Deep Learning for Recommender Systems: A Survey of the State-of-the-Art
    3. Wide & Deep Learning for Recommender Systems
    4. Attention-based Deep Learning for Recommendation Systems: A Survey
    5. Sequential Recommendation with Recurrent Neural Networks
    6. Variational Autoencoders for Collaborative Filtering
    7. Graph Convolutional Neural Networks for Recommendation Systems: A Survey

    AI recommended 7 alternatives but never named wzhe06/Reco-papers. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 wzhe06/Reco-papers?
    pass
    AI named wzhe06/Reco-papers explicitly

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

  • If a team adopts wzhe06/Reco-papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named wzhe06/Reco-papers 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 wzhe06/Reco-papers solve, and who is the primary audience?
    pass
    AI did not name wzhe06/Reco-papers — likely talking about a different project

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

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wzhe06/Reco-papers — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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