Matching "fuzzy" data based on several inputs

I have a search and matching problem:

Inputs

In my database, I have thousands of names, in addition to some other matching characteristics: a few columns of numerical data, and a few columns of other text that helps identify this specific company.

A prospective client has about 500 company names, and then sparsely populated additional ch开发者_JAVA技巧aracteristics as mentioned above for each of the names.

Current Process

In the past, the process has been a manual one, try to match each name given by the client by searching through the database, finding a name "like" the one reported to me, and then verifying that the additional characteristics match up. However, the main issue is that the names reported are not the same, can often contain abbreviations or only parts of the name stored in my database, and the additional characteristics may be incomplete or only partially matching as well.

Automation

I want to automate this process since it happens frequently. The optimal solution would input one company from the client list along with any of the additional characteristics they filled in for it, and then try to find the top 5 matches in my database.

I've never used Lucene or Sphinx, but they seem to be more document driven. Is there a way to format these inputs so those libraries work for this problem, or instead, what other software tools exist that would work?

To Lucene, a 'document' can easily be a row in a table and I think you will like the fuzzy~ search and search hit scoring capabilities.