Robust, Scalable Detection of Text Containment in Large Web-Crawled Corpora
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Computer Science > Computation and Language
Title:Robust, Scalable Detection of Text Containment in Large Web-Crawled Corpora
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).
| Comments: | 6 pages + references and appendices |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2607.10020 [cs.CL] |
| (or arXiv:2607.10020v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2607.10020
arXiv-issued DOI via DataCite (pending registration)
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