RRepoGEO

REPOGEO REPORT · LITE

shenweichen/AlgoNotes

Default branch main · commit 892f0d01 · scanned 5/19/2026, 10:18:01 AM

GitHub: 1,820 stars · 245 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
30 /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
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 shenweichen/AlgoNotes, 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

    Why:

    CURRENT
    # 浅梦学习笔记 公众号文章汇总
    COPY-PASTE FIX
    # 浅梦学习笔记：推荐系统、计算广告、大数据等领域学习笔记与文章汇总
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    recommendation-systems, machine-learning, deep-learning, algorithms, data-science, computational-advertising, nlp, computer-vision, graph-algorithms, big-data, interview-preparation, learning-notes, study-notes, knowledge-base
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the root of the repository with the text of the MIT License.

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 shenweichen/AlgoNotes
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Apache Kafka
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Apache Kafka · recommended 2×
  2. Apache Flink · recommended 2×
  3. Apache Spark (MLlib) · recommended 1×
  4. Pandas · recommended 1×
  5. Feast · recommended 1×
  • CATEGORY QUERY
    What are effective strategies for improving ranking and conversion rate prediction in recommendation systems?
    you: not recommended
    AI recommended (in order):
    1. Apache Spark (MLlib)
    2. Pandas
    3. Feast
    4. Tecton
    5. TensorFlow
    6. PyTorch
    7. LightGBM
    8. XGBoost
    9. Surprise
    10. Ray RLlib
    11. OpenAI Gym
    12. VWO
    13. Optimizely
    14. MLflow
    15. Apache Kafka
    16. Apache Flink
    17. Redis
    18. Memcached
    19. Fairlearn
    20. Aequitas

    AI recommended 20 alternatives but never named shenweichen/AlgoNotes. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking comprehensive learning notes on recommendation algorithms, user features, and computational advertising.
    you: not recommended
    AI recommended (in order):
    1. Recommender Systems Handbook
    2. Deep Learning for Recommender Systems
    3. Mining of Massive Datasets
    4. Computational Advertising: Techniques for Targeting and Ranking in Online Ad Systems
    5. Reinforcement Learning for Recommender Systems
    6. Designing Data-Intensive Applications
    7. Apache Kafka
    8. Apache Flink

    AI recommended 8 alternatives but never named shenweichen/AlgoNotes. 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 shenweichen/AlgoNotes?
    pass
    AI named shenweichen/AlgoNotes explicitly

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

  • If a team adopts shenweichen/AlgoNotes in production, what risks or prerequisites should they evaluate first?
    pass
    AI named shenweichen/AlgoNotes 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 shenweichen/AlgoNotes solve, and who is the primary audience?
    pass
    AI named shenweichen/AlgoNotes explicitly

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

Embed your GEO score

Drop this badge into the README of shenweichen/AlgoNotes. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/shenweichen/AlgoNotes.svg)](https://repogeo.com/en/r/shenweichen/AlgoNotes)
HTML
<a href="https://repogeo.com/en/r/shenweichen/AlgoNotes"><img src="https://repogeo.com/badge/shenweichen/AlgoNotes.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

shenweichen/AlgoNotes — 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