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<!DOCTYPE html>
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<title>LEMMA-RCA| A Large Collection of Multi-modal Multi-domain Datasets for Root Cause Analysis</title>
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<h1 style="font-family: 'Merienda', cursive;color:white;">LEMMA-RCA</h1>
<p style="font-family: 'Merienda', cursive;color:white;"><strong>Multi-modal Datasets for Root Cause Analysis<strong></p>
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Root cause analysis (RCA) is a task of identifying the underlying causes of system faults/failures by analyzing the system monitoring data. LEMMA-RCA is a collection of multi-modal datasets with various real system faults to facilitate future research in RCA. It is multi-domain, consisting of real-world applications such as microservice and water treatment/distribution systems. The datasets are released under the CC BY-NC 4.0 license and hosted on Huggingface, the codes are available on Github.
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<h3 class="text-center"><a href="#"> Multiple Domains</a></h3>
<p class="f3-light">LEMMA-RCA covers two domains: IT Operations (Product Review and Cloud Computing) and OT Operations (Water Treatment/Distribution). Each domain contains two datasets.</p>
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<h3 class="text-center"><a href="#">Real System Faults</a></h3>
<p class="f3-light"> Each dataset contains various system faults simulated from real-world scenarios. For details, please check our Github page.</p>
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<h3 class="text-center"><a href="/docs/benchmark.html"> Unified Evaluation</a></h3>
<p class="f3-light"> LEMMA-RCA datasets are evaluated with eight causal learning baselines in four settings: online/offline with single/multiple modality data. </p>
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<h3>Citation</h3>
<p>If you use LEMMA-RCA in your work, please cite <a href="https://arxiv.org/abs/2406.05375">our paper</a></p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code style="text-align: left;">
@misc{zheng2024lemmarca,
title={LEMMA-RCA: A Large Multi-modal Multi-domain Dataset for Root Cause Analysis},
author={Lecheng Zheng, Zhengzhang Chen, Dongjie Wang, Chengyuan Deng, Reon Matsuoka, and Haifeng Chen},
year={2024},
eprint={2406.05375},
archivePrefix={arXiv},
primaryClass={cs.AI}
}
</code></pre></div></div>
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