hashing strings

I have streaming strings (text containing words and number).

Taking one line at a time for streaming strings, I would like to assign a unique value to them.

the examples may be:strings with their 开发者_运维百科scores/hash

  User1 logged in Comp1 port8087       1109      
  User2 logged in comp2                1135
  user3 logged in port8080             1098
  user1 logged in comp2 port8080       1178       

these string should be in same cluster. For this what i have thought is mapping(bad type of hashing) the strings such that the small change in the string wont affect the score that much.

One simple way of doing that may be: taking UliCp8, Ulic .... ( i.e. 1st letter of each sentence) and find some way of scoring. After then the similar scored strings are kept in same bucket and later on sub group them.

The improved method would be: lets not take out first word of each word of the string but find some way to take representative value of the word such that the string representation may be quite suitable for mapping with score/hash as i mention.

Considering Levenstein distance or jaccard_index or some similarity distance metrices, all of them require inputting the strings for comparisions. Isn't there any method to hash/score the string as stated without going for comparisions.( POS tagging, comparing looks uneffiecient for my purpose as the data are streaming, huge in number, unstructured)

Hope you understand what i want to achieve and please help me out. Forgot about the comments below and lets restart.

"at least two similar word (not considering length) should have similar hash value"

This is against the most basic requirements for a hash function. With a hash function also minimal changes to the input should produce vehement changes to the bucket the hash falls into.

You are looking for an algorithm that calculates the similarity or distance between two inputs.

As stated you are not looking for a hash function, rather something like the Levenshtein distance which is an algorithm for calculating a metric representing the degree of differences between two sequences of bits. It is commonly used to find out how similar/dissimilar two strings are. Hashing / message digests are good for creating identifiers for unique, distinct values but they will produce entirely different results for "similar" values.

You are interested in the similarity of strings. Here is a nice post that names a few resources that are used for measuring string similarity. Maybe Lucene could help you in your situation.