RRepoGEO

REPOGEO REPORT · LITE

linwhitehat/ET-BERT

Default branch main · commit 42b950bd · scanned 6/5/2026, 1:58:12 PM

GitHub: 645 stars · 127 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 linwhitehat/ET-BERT, 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
    Clarify project domain in README's opening sentence

    Why:

    CURRENT
    The repository of ET-BERT, a network traffic classification model on encrypted traffic.
    COPY-PASTE FIX
    ET-BERT is a network traffic classification model designed for encrypted traffic, leveraging pre-trained transformers. This repository provides the official implementation for our WWW 2022 accepted paper.
  • mediumtopics#2
    Add 'network-traffic-classification' to repository topics

    Why:

    CURRENT
    burst-analysis, encrypted-traffic-analysis, mask-burst-modeling, pre-training, pytorch, same-origin-burst-prediction, transformer-architecture
    COPY-PASTE FIX
    burst-analysis, encrypted-traffic-analysis, mask-burst-modeling, network-traffic-classification, pre-training, pytorch, same-origin-burst-prediction, transformer-architecture
  • mediumhomepage#3
    Add project homepage to About section

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2202.06335

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 linwhitehat/ET-BERT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 2×
  2. Scikit-learn · recommended 1×
  3. TShark · recommended 1×
  4. DPDK · recommended 1×
  5. TensorFlow · recommended 1×
  • CATEGORY QUERY
    How can I classify encrypted network traffic using modern machine learning techniques?
    you: not recommended
    AI recommended (in order):
    1. Scikit-learn
    2. TShark
    3. DPDK
    4. TensorFlow
    5. Keras
    6. PyTorch
    7. Zeek
    8. Bro
    9. Apache Spark MLlib
    10. NVIDIA RAPIDS
    11. cuML
    12. cuDF
    13. Wireshark

    AI recommended 13 alternatives but never named linwhitehat/ET-BERT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a PyTorch-based solution for identifying encrypted traffic patterns with transformer architectures.
    you: not recommended
    AI recommended (in order):
    1. DeepPacket
    2. PyTorch
    3. Hugging Face Transformers Library
    4. BERT-like models
    5. PyTorch-Transformers (custom implementation)
    6. torch.nn.Transformer
    7. timm

    AI recommended 7 alternatives but never named linwhitehat/ET-BERT. 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 linwhitehat/ET-BERT?
    pass
    AI named linwhitehat/ET-BERT explicitly

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

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

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

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linwhitehat/ET-BERT — 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