RRepoGEO

REPOGEO REPORT · LITE

lixus7/Time-Series-Works-Conferences

Default branch main · commit 6afa202d · scanned 6/14/2026, 1:03:05 AM

GitHub: 961 stars · 96 forks

AI VISIBILITY SCORE
22 /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
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 lixus7/Time-Series-Works-Conferences, 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
    Add a clear 'Purpose' section at the top of the README

    Why:

    CURRENT
    The README currently starts with '## About Me (Du Yin)' after the main title.
    COPY-PASTE FIX
    Add a section immediately after the main title, e.g., '## Purpose
This repository serves as a comprehensive, curated summary of recent and impactful time-series research works presented at top computer science conferences (e.g., NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE). It aims to provide researchers and students with a centralized resource for understanding cutting-edge advancements in time-series analysis and deep learning.'
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/lixus7/Time-Series-Works-Conferences
  • lowtopics#3
    Add more descriptive topics to clarify the repo's nature as a research summary

    Why:

    CURRENT
    accident-detection, anomaly-detection, deep-learning, demand-forecasting, location, multivariate-timeseries, paper-list, probabilistic-models, spatio-temporal, spatio-temporal-data, spatio-temporal-modeling, spatio-temporal-prediction, time-series, time-series-forecasting, time-series-imputation, time-series-prediction, traffic-prediction, travel-time-prediction
    COPY-PASTE FIX
    accident-detection, anomaly-detection, deep-learning, demand-forecasting, location, literature-review, multivariate-timeseries, paper-list, probabilistic-models, research-summary, spatio-temporal, spatio-temporal-data, spatio-temporal-modeling, spatio-temporal-prediction, time-series, time-series-forecasting, time-series-imputation, time-series-prediction, traffic-prediction, travel-time-prediction

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 lixus7/Time-Series-Works-Conferences
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Papers With Code
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Papers With Code · recommended 1×
  2. NeurIPS · recommended 1×
  3. ICML · recommended 1×
  4. ICLR · recommended 1×
  5. KDD · recommended 1×
  • CATEGORY QUERY
    Where can I find a summary of recent time series research from top conferences?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. NeurIPS
    3. ICML
    4. ICLR
    5. KDD
    6. ACM Digital Library
    7. AAAI
    8. IJCAI
    9. AAAI Digital Library
    10. arXiv.org
    11. GitHub
    12. The Batch
    13. DeepLearning.AI
    14. Two Minute Papers
    15. Yannic Kilcher
    16. Twitter
    17. LinkedIn
    18. Google Scholar
    19. Semantic Scholar

    AI recommended 19 alternatives but never named lixus7/Time-Series-Works-Conferences. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the cutting-edge deep learning techniques for spatio-temporal data and forecasting?
    you: not recommended
    AI recommended (in order):
    1. DCRNN
    2. STGCN
    3. ASTGCN
    4. Informer
    5. Autoformer
    6. PatchTST
    7. FNO
    8. PINNs

    AI recommended 8 alternatives but never named lixus7/Time-Series-Works-Conferences. 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 lixus7/Time-Series-Works-Conferences?
    pass
    AI did not name lixus7/Time-Series-Works-Conferences — 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 lixus7/Time-Series-Works-Conferences in production, what risks or prerequisites should they evaluate first?
    pass
    AI named lixus7/Time-Series-Works-Conferences 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 lixus7/Time-Series-Works-Conferences solve, and who is the primary audience?
    pass
    AI did not name lixus7/Time-Series-Works-Conferences — 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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  • Brand-free category queries5 vs 2 in Lite
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