Beefy Boxes and Bandwidth Generously Provided by pair Networks
Problems? Is your data what you think it is?

Re: Brainstorming session: detecting plagiarism

by blokhead (Monsignor)
on Jun 08, 2005 at 20:10 UTC ( #464824=note: print w/replies, xml ) Need Help??

in reply to Brainstorming session: detecting plagiarism

I like the idea of comparing each pair of sentences for similarity. There are several metrics for sentence similarity that come to mind:

Edit distance & longest-common subsequence. These two are pretty similar: look for an edit distance less than a certain percent of the sentence length, or an LCS larger than a certain percent.

As you are doing now, I would do this on a word-by-word basis, and not character-by-character. However, these algorithms can be generalized a bit, so that instead of each pair of words either agreeing or disagreeing, each pair can have a fractional level of agreement between 0 and 1. If you implemented a "synonym measurer", you could easily plug this into such generalized LCS/Levenshtein algorithms. (This could also quite easily encompass changes in word stemming as well as synonimity.)

Another metric you can use for sentence similarity is Zaxo's favorite method: using compression & information theory, although you may not be able to pull out as much information about *how* the sentences are similar as in the algorithms above.


  • Comment on Re: Brainstorming session: detecting plagiarism

Log In?

What's my password?
Create A New User
Node Status?
node history
Node Type: note [id://464824]
[Corion]: A good morning!

How do I use this? | Other CB clients
Other Users?
Others taking refuge in the Monastery: (5)
As of 2017-10-20 06:20 GMT
Find Nodes?
    Voting Booth?
    My fridge is mostly full of:

    Results (259 votes). Check out past polls.