FindMyText: Robust, Scalable Detection of Text Containment in Large Web-Crawled Corpora

• URL: http://arxiv.org/abs/2607.10020v2
• Date: Wed, 15 Jul 2026 18:51:10 GMT
• Title: FindMyText: Robust, Scalable Detection of Text Containment in Large Web-Crawled Corpora
• Abstract summary: FindMyText is a Python package designed to efficiently assess whether a given text appears, in part or in full, within a text corpus.<n>The tool builds on prior techniques for document fingerprinting, but extends them with a novel mechanism to explicitly capture sequences of matching fingerprints.<n>It can more reliably detect near-verbatim copies of a given text rather than mere textual similarities.
• Score: 3.678882282826422
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present FindMyText, an open-source Python package designed to efficiently assess whether a given text appears, in part or in full, within a text corpus. The tool builds on prior techniques for document fingerprinting, but extends them with a novel mechanism to explicitly capture sequences of matching fingerprints. By identifying such chains, the tool can more reliably detect near-verbatim copies of a given text rather than mere textual similarities. This makes FindMyText particularly suited for verifying the presence of copyrighted material in a corpus. Leveraging a distributed, disk-based indexing framework, the system scales to large web-crawled datasets. Using a new benchmark for evaluating text containment methods, we show that FindMyText outperforms alternative approaches across three datasets (ArXiv papers, Wikipedia, and generic web content).

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