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Technical Perspective: Unicorn: A Unified Multi-Tasking Matching Model

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AnHai DoanAuthors Info & Claims

ACM SIGMOD Record, Volume 53, Issue 1

Page 43

https://doi.org/10.1145/3665252.3665262

Published: 14 May 2024 Publication History

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Abstract

Data integration has been a long-standing challenge for data management. It has recently received significant attention due to at least three main reasons. First, many data science projects require integrating data from disparate sources before analysis can be carried out to extract insights. Second, many organizations want to build knowledge graphs, such as Customer 360s, Product 360s, and Supplier 360s, which capture all available information about the customers, products, and suppliers of an organization. Building such knowledge graphs often requires integrating data from multiple sources. Finally, there is also an increasing need to integrate a massive amount of data to create training data for AI models, such as large language models.

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ACM SIGMOD Record Volume 53, Issue 1

March 2024

90 pages

DOI:10.1145/3665252

Editor:
Rada Chirkova
North Carolina State University

Issue’s Table of Contents

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 14 May 2024

Published in SIGMOD Volume 53, Issue 1

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A unified scaling model in the era of big data analytics

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