About this Plagiarism Checker — What it does and how to use it
This Plagiarism Checker is built to help creators, teachers, editors, and students quickly compare a document against one or more known reference texts. It runs entirely in the user's browser for local comparisons and privacy: you paste or upload the document to check, then add any reference texts (for example, lecture notes, previously submitted work, source documents, or material you want to check against). The tool performs an algorithmic comparison using word-shingles and fuzzy matching to detect overlapping passages and quantify similarity. It highlights matched snippets, reports a similarity percentage, and allows exporting a simple report for review.
How it works (brief): the input text is normalized (lowercased, punctuation trimmed) and split into overlapping sequences of words called shingles (default size 6 words). Each shingle is hashed and stored in a set. For every reference text added, the tool builds the same set of shingles and computes a Jaccard similarity — the size of the intersection divided by the size of the union of shingles — to provide a baseline similarity percentage. Additionally, the checker searches for longest common substrings to find longer exact or near-exact matches and extracts those snippets for display. You can tune the shingle size and snippet threshold to make the detection more or less strict.
Important limitations: this client-side checker does not search the open web. It cannot find instances of your text that exist only on external websites, academic repositories, or subscription databases unless you supply those texts as references or use a server-side plagiarism API that crawls or queries those sources. For institution-grade checks, use a commercial plagiarism detection API or service, which can search the web, journals, and student submission archives. The local checker excels as a privacy-friendly pre-screen: it finds reuse against internal documents, known sources, and pasted content without sending data to external servers.
Interpreting scores: similarity percentages are indicators, not absolute proof of plagiarism. High similarity may indicate copied passages, but it can also reflect legitimate quotation, shared boilerplate, references, or correctly attributed text. Always inspect the highlighted snippets and check context: are the matches properly quoted and cited? Are short common phrases inflating the score? Adjust the shingle size and snippet threshold: larger shingles reduce noise from short common phrases and increase precision for longer copied passages.
Best practices: before concluding plagiarism, review the matches manually and verify citations. Use this tool to quickly surface suspicious overlap, then combine results with human judgment or a web-scale scan if needed. When implementing on a website, consider adding an optional server integration that calls a trusted plagiarism API for full web coverage. The UI already supports an optional URL field where you can paste authoritative sources; a server could fetch and add those pages as references automatically.
Privacy & security: this tool is designed to work locally — nothing is uploaded to a third-party service unless you explicitly wire one in. If you add server integration, ensure you follow data protection rules and clarify terms for students or users about how submissions are stored and used.
In short: use this checker as a fast, private, and configurable local comparison utility. It is excellent for instructors comparing a submission to lecture slides, for editors checking an article against supplied sources, or for writers self-auditing drafts. For exhaustive web checks, pair it with a verified plagiarism API.
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