RRepoGEO

REPOGEO REPORT · LITE

grahamjenson/list_of_recommender_systems

Default branch master · commit 966106a6 · scanned 5/12/2026, 5:02:51 AM

GitHub: 4,831 stars · 705 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 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 grahamjenson/list_of_recommender_systems, 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
  • highreadme#1
    Reposition the README H1 to specify category and scope

    Why:

    CURRENT
    # List of Recommender Systems
    COPY-PASTE FIX
    # Curated List and Comparison of Recommender Systems (SaaS, Open-Source, and Research)
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    recommender-systems, recommendation-engine, saas, e-commerce, comparison, curated-list, machine-learning, ai, product-recommendations
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    (Choose an appropriate open-source license like MIT or Apache-2.0 and add it to a LICENSE file in the repository root.)

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 grahamjenson/list_of_recommender_systems
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Gartner Magic Quadrant for Digital Commerce
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Gartner Magic Quadrant for Digital Commerce · recommended 1×
  2. Forrester Wave: Experience Optimization Platforms · recommended 1×
  3. Papers With Code - Recommendation Systems · recommended 1×
  4. AWS Machine Learning Blog · recommended 1×
  5. Google Cloud AI Blog · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive comparison of various recommendation engine solutions?
    you: not recommended
    AI recommended (in order):
    1. Gartner Magic Quadrant for Digital Commerce
    2. Forrester Wave: Experience Optimization Platforms
    3. Papers With Code - Recommendation Systems
    4. AWS Machine Learning Blog
    5. Google Cloud AI Blog
    6. Azure AI Blog
    7. Amazon Personalize
    8. Sagemaker
    9. Google Cloud Recommendations AI
    10. Vertex AI
    11. Kaggle Discussions and Notebooks
    12. Surprise
    13. LightFM
    14. implicit
    15. Medium Articles and Data Science Blogs
    16. Towards Data Science
    17. Analytics Vidhya
    18. RecBole

    AI recommended 18 alternatives but never named grahamjenson/list_of_recommender_systems. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best plug-and-play SaaS options for adding product recommendations to my e-commerce site?
    you: not recommended
    AI recommended (in order):
    1. Nosto
    2. Dynamic Yield
    3. Barilliance
    4. Recombee
    5. Algolia Recommend
    6. Segmentify

    AI recommended 6 alternatives but never named grahamjenson/list_of_recommender_systems. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 grahamjenson/list_of_recommender_systems?
    pass
    AI did not name grahamjenson/list_of_recommender_systems — 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?

  • If a team adopts grahamjenson/list_of_recommender_systems in production, what risks or prerequisites should they evaluate first?
    pass
    AI named grahamjenson/list_of_recommender_systems 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 grahamjenson/list_of_recommender_systems solve, and who is the primary audience?
    pass
    AI did not name grahamjenson/list_of_recommender_systems — 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?

Embed your GEO score

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