[Corpora-List] semantic similarity

[Antoinette Renouf]

Dear Jana
We developed a system called ACRONYM to do this, in 1994-7.
See http://rdues.uce.ac.uk/acronym.shtml for overview and demo.
Regards
Antoinette

--------------------------

Antoinette Renouf
Professor of English Language and Linguistics
School of English
University of Central England in Birmingham
Perry Barr
Birmingham B42 2SU
 
tel: +44 (0)121 331 7230
fax: +44 (0)121 331 6622
mob: +44 (0)7980 750037
email: ajrenouf at uce.ac.uk
url: http://rdues.uce.ac.uk
 
http://www.webcorp.org.uk/ 

-----Original Message-----
From: owner-corpora at lists.uib.no [mailto:owner-corpora at lists.uib.no] On
Behalf Of Jana Diesner
Sent: 20 January 2005 16:36
To: CORPORA at hd.uib.no
Subject: [Corpora-List] semantic similarity

Dear list members,

We are looking for strategies, algorithms or code to automatically find
single terms or multiple adjacent terms that are semantically similar
within
and across documents. The approach must not require POS tagging or an
initial input of a reference term to the system. The resulting clusters
of
semantically similar terms suggested by the system do not need to be
exclusive. We are familiar with secondstring, the software developed by
William Cohen, and semantic similarity based on string-edit distances.



Thank you very much.

Jana



____________________

Jana Diesner
Carnegie Mellon University

jdiesner at andrew.cmu.edu