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Written in native Rust, it offers fast execution and low memory overhead, with no dependencies on external runtime environments. Using the [`textract`](https://crates.io/crates/textract), [`rtf-parser`](https://crates.io/crates/rtf-parser), and [`epub`](https://crates.io/crates/epub) crates to parse various text file formats, it uses SimHash to quickly filter out highly dissimilar documents then applies a more sophisticated MinHash algorithm to identify near-duplicates with high accuracy.\n\nInspired by [Dr. Pawe\u0026#322; Mandera](https://github.com/pmandera)'s near-duplicate detection tool [*Duometer*](https://github.com/pmandera/duometer), *ShadowSeek* aims to provide a more lightweight and efficient alternative. Development in Rust allows users to run a precompiled binary without needing to install a Java runtime environment; as an added bonus, this also reduces startup time and memory usage. The inclusion of SimHash as a first-pass filter also facilitates faster elimination of dissimilar documents, minimizing the number of comparisons performed in the more computationally expensive MinHash stage.\n\n**(CURRENTLY UNDER DEVELOPMENT)**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fluis-varona%2Fshadowseek","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fluis-varona%2Fshadowseek","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fluis-varona%2Fshadowseek/lists"}