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<!DOCTYPE html>
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<meta name="description" content="Efficient In-Memory Inverted Indexes: Theory and Practice.">
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<meta name="keywords" content="Inverted Indexes, Information Retrieval, Search Engines">
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<title>Efficient In-Memory Inverted Indexes: Theory and Practice</title>
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More Research
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HyperNeRF
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Nerfies
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<h1 class="title is-1 publication-title">Practical, Efficient, In-Memory Inverted Indexes/h1>
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<div class="is-size-5 publication-authors">
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<span class="author-block">
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<table>
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<td class="profile-cell"><img class="profile-img" src="static/images/joel.png"
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alt="Profile Jel"></td>
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<td class="profile-cell"><img class="profile-img" src="static/images/sean.png"
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alt="Profile Sean"></td>
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<td class="profile-cell"><img class="profile-img"
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src="static/images/antonio.png" alt="Profile Antonio"></td>
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<td class="profile-cell"><img class="profile-img" src="static/images/michal.png"
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alt="Profile Michal"></td>
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</tr>
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<tr>
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<!-- <th scope="row">TR-7</th> -->
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<td width="20%" style="text-align: center"><a href="https://jmmackenzie.io"
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style="border-radius: 50%">Joel Mackenzie</a><sup>1</sup></td>
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<td width="20%" style="text-align: center"><a href="https://macavaney.us"
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style="border-radius: 50%">Sean MacAvaney</a><sup>2</sup></td>
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<td width="20%" style="text-align: center"><a href="https://antoniomallia.it"
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style="border-radius: 50%">Antonio Mallia</a><sup>3</sup></td>
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<td width="20%" style="text-align: center"><a href="https://siedlaczek.me/"
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style="border-radius: 50%">Michal Siedlaczek</a><sup>4</sup></td>
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</tr>
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</table>
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</div>
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<div class="is-size-5 publication-authors">
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<span class="author-block"><sup>1</sup>The University of Queensland,</span>
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<span class="author-block"><sup>2</sup>University of Glasgow,</span>
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<span class="author-block"><sup>3</sup>Seltz,</span>
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<span class="author-block"><sup>4</sup>MongoDB, Inc.</span>
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</div>
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<br />
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<div class="is-size-5 publication-authors">
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<b>Date and Location: ECIR 2026, Delft, Netherlands - Sunday March 30th, 09.00-12.30</b>
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</div>
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<a href="https://arxiv.org/abs/2011.12948"
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class="external-link button is-normal is-rounded is-dark">
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<!-- Abstract. -->
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<h2 class="title is-3">Abstract</h2>
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<div class="content has-text-justified">
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<p>
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Inverted indexes are the backbone of most large-scale information retrieval systems.
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Although conceptually simple, high-performance inverted indexes require a deep understanding
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of low-level system optimizations, compression techniques, and traversal strategies. With
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the widespread adoption of in-memory search engines, the rise of learned sparse retrieval
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(LSR), and the increasing complexity of ranking pipelines, the design space for efficient
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indexing and retrieval systems has expanded significantly.
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</p>
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<p>
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This tutorial addresses a critical knowledge gap between textbook-style explanations and
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advanced techniques required for efficient and optimized retrieval. It aims to equip
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researchers and practitioners with a comprehensive understanding of how modern in-memory
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search systems are designed, built, and optimized for high-performance retrieval across
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large-scale document collections.
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</p>
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<h2 class="title is-3">Practical Component</h2>
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<div class="content has-text-justified">
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<p>
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For the practical component, we will need to grab some data, and have some instructions ready.
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</p>
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<p>
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<strong>Prerequisite:</strong> You have your own machine with Docker installed.
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<br>
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I will step through on my own machine if you don’t have access.
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</p>
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<p>
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You can also experiment with the tutorial at any time (later).
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</p>
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<p>
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<strong>Tutorial:</strong> <a href="https://shorturl.at/VExpG" target="_blank">https://shorturl.at/VExpG</a>
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<br>
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<strong>AKA:</strong> <a href="https://github.com/pisa-engine/pisa/blob/main/test/docker/tutorial/instructions.md" target="_blank">
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https://github.com/pisa-engine/pisa/blob/main/test/docker/tutorial/instructions.md</a>
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</p>
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<p>
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<strong>Slide Deck:</strong> <a href="https://pisa-engine.github.io/static/SIGIR2025-2.pdf" target="_blank">https://pisa-engine.github.io/static/SIGIR2025-2.pdf</a>
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