<p>Check out google similarity distance - <a href="http://arxiv.org/abs/cs.CL/0412098" rel="noreferrer">http://arxiv.org/abs/cs.CL/0412098</a>
eg. if lots of webpages include them both, theyre probably related. </p>

<p>demo program at <a href="http://mechanicalcinderella.com" rel="noreferrer">http://mechanicalcinderella.com</a></p>

<p>Other than that, you could try to translate a project like wordnet ((google translate could help), or start a collaborative ontology.</p>
NLP: any easy and good methods to find semantic similarity between words?
<p>I don't know whether StackOverflow covers NLP, so I am gonna give this a shot.
I am interested to find the semantic relatedness of two words from a specific domain, i.e. "image quality" and "noise".  I am doing some research to determine if reviews of cameras are positive or negative for a particular attribute of the camera.  (like image quality in each one of the reviews). </p>

<p>However, not everybody uses the exact same wording "image quality" in the posts, so I am out to see if there is a way for me to build something like that:</p>

<p>"image quality" which includes ("noise", "color", "sharpness", etc etc) 
so I can wrap all everything within one big umbrella.</p>

<p>I am doing this for another language, so Wordnet is not necessarily helpful. And no, I do not work for Google or Microsoft so I do not have data from people's clicking behaviour as input data either.      </p>

<p>However, I do have a lot of text, pos-tagged, segmented etc.          </p>