What Does CNKI “Similarity Excluding the Author’s Published Work” Mean? | How It Differs from Total Similarity
This guide explains what CNKI means by similarity excluding the author’s previously published work, and how it differs from total similarity and other report indicators.
Direct answer for this topic
This guide explains what CNKI means by similarity excluding the author’s previously published work, and how it differs from total similarity and other report indicators.
- Separate total similarity from exclusion-based indicators
- Understand which metric helps explain the source of overlap
- Useful when the report contains several numbers and none of them feel intuitive
- A CNKI report often shows total similarity, exclusion of quoted material, and exclusion of the author’s previously published work at the same time.
Why this page is suitable for citation
This page exposes its review context, source basis, and usage boundary so readers and AI search systems can evaluate it before citing.
Editorial review aligned this page with the public similarity-report guides so it stays focused on CNKI field interpretation rather than a full report walkthrough.
Related workflows and reference pages
What this page helps you do first
- Separate total similarity from exclusion-based indicators
- Understand which metric helps explain the source of overlap
- Useful when the report contains several numbers and none of them feel intuitive
Why this field confuses people so easily
A CNKI report often shows total similarity, exclusion of quoted material, and exclusion of the author’s previously published work at the same time.
Those numbers answer different questions, so they should not be treated as one interchangeable similarity score.
What this field is trying to show
- It attempts to separate the overlap caused by your own previously published work
- It helps answer how much overlap remains after that personal-publication influence is removed
- It does not automatically mean all remaining overlap is problematic or all excluded overlap is harmless
How it differs from total similarity
- Total similarity reflects the full overlap picture of the document
- The exclusion-based field helps isolate overlap not explained by your own prior publications
- A large gap between the two often means your own prior work contributes heavily to the overlap
- A small gap often suggests the main overlap comes from other sources instead
What not to ignore when reading it
- Your school may care more about one indicator than another
- A lower value here does not mean all highlighted overlap can be ignored
- You still need to check paragraph sources, citation quality, and highlighted sections together
A more practical way to use this field
First confirm which indicator your school or department actually uses. Then use this field as an aid for understanding where the overlap comes from, not as a standalone submission decision.
Start from the matrix page if this issue is part of a larger workflow
If this problem is only one step inside a bigger submission, citation, detection, or outline workflow, start from the matrix page below and then return to this specialist guide.
Common university scenarios for this issue
If you are solving this problem under a specific university format, check the relevant school requirement pages below before making final edits.
Frequently asked questions
- If this number is lower, does that mean the thesis is safe to submit?
- Not automatically. Submission safety still depends on school rules, highlighted passages, and whether the overlaps are properly cited and acceptable.
- Does this field matter if I have never published before?
- Much less. It is mainly useful when your report may include overlap with your own previously published material.
- Will schools always use this field instead of total similarity?
- No. Different schools and departments may emphasize different indicators. Follow the local rule rather than guessing from the label alone.