Cliché Detection
I was recently reading a pretty bad book that contained many clichés when the thought occurred to me that it might be fun, after learning more about NLP and provided with the right data, to write a program to scan a document and return likely cliché phrases found within it.

I've never done anything like this before and am wondering if I could be pointed in the direction of texts, algorithms, data sets, and/or approaches that might help me to solve this problem.

I came across a [Google Books Ngrams data set][1] that looks possibly useful, but it left me with questions about how to best tokenize a digital work of fiction, how to compare it against the provided n-grams, score possible clichés, etc.

Any help at all would be greatly appreciated, and my apologies in advance for the rather abstract question.

Thanks!


  [1]: http://aws.amazon.com/datasets/8172056142375670
Cliché Detection
===

I was recently reading a pretty bad book that contained many clichés when the thought occurred to me that it might be fun, after learning more about NLP and provided with the right data, to write a program to scan a document and return likely cliché phrases found within it.

I've never done anything like this before and am wondering if I could be pointed in the direction of texts, algorithms, data sets, and/or approaches that might help me to solve this problem.

I came across a [Google Books Ngrams data set][1] that looks possibly useful, but it left me with questions about how to best tokenize a digital work of fiction, how to compare it against the provided n-grams, score possible clichés, etc.

Any help at all would be greatly appreciated, and my apologies in advance for the rather abstract question.

Thanks!


  [1]: http://aws.amazon.com/datasets/8172056142375670