How to perform Cleaning of a very large set of addresses I have a dataset where I have a large number of addresses. The problem lies in the fact that many addresses although they are same but haven't been noted down in the same manner. So I want to find these addresses which are similar and clean my data from the duplicate data. 

Is there any standard approach or algorithms that can help me? How should I go about this problem?
I guess you are in a situation that different fields of an address are mixed together. Try break the address text into Shingles and then try Locality-sensitive Hashing

Prof. Jeff Ullman's Text Book may help you put together all the techniques you need, starts with Section 3.2