I have a large table of attributes of different real-world movie theaters. I have classified them by the "true" physical entity to which they belong, so that there may be multiple records for a given movie theater entity.
In this table, I have information such as names, how many screens they have, etc. Given some identifying information (part of the name, one line of the address and number of screens, say) I would like to classify the given information to the entity with which it is associated, and add it to the database.
I was thinking of using an algorithm such as nearest neighbour but the choice of distance metric seems limiting. The only implementations I have seen use all numeric or all text information to calculate distance.
How would I calculate a distance metric for data that may be numeric, text and categorical in nature?