Matching observations based on similarity of categorical variables - sql

Question

I was wondering, if someone has a good way how to match two observations based on categorical (non-ordinal) variables.
The exercise I am working on is matching mentees with mentors based on interests and other characteristics that are (non-ordinal or ordinal) categorical variables.
Variable Possible Values
Sport “Baseball”, “Football”, “Basketball” (…)
Marital Status “Single, no kids”, “Single, young kids”, “Married, no kids”, “Married, young kids”, (…)
Job Level 1, 2, 3, 4, 5, 6
Industry “Retail”, “Finance”, “Wholesale”, (…)
There are also indicators if any of the variables is important to the person. I understand, I could force marital status into one or two ordinal variables like (“Single”, “Married”, “Widow”) and (“no kids”, “young kids”, “grown kids”). But I don’t know how to handle industry and sport as there is no logical order to them. My plan was originally to use a clustering technique to find a match between the mentor and the mentee set based on the shortest distance or the given points. But that would ignore the fact that people could decide, if the variable is important to them or not (“Yes”, “No”).
Now, I am thinking to just brute force logic on it by using nested IF statements that check, if there is a perfect match based on the importance and the actual values. ELSE check if there is a matching record that has all matches, but one category etc. This seems very inefficient, so I was hoping if someone came across a similar problem, I would find a better way how to handle this.
Would it make sense to create two variables one for the importance sequence (eg: "YesNoYesNoNo") and one for the interests (eg "BasketballSingleNokids6Retail") and then employ fuzzy matching?
Best regards,

Answer 1

One approach would be to decide first on which variables you must have an exact match, do a cartesian join on those, then generate a score based on other non-mandatory matches and output records where the score exceeds a threshold. The more mandatory matches you require, the better the query will perform.
E.g.
%let MATCH_THRESHOLD = 2; /*At least this many optional variables must match*/
proc sql;
create table matches as
select * from mentors a inner join mentees b
/*Mandatory matches*/
on a.m_var1 = b.m_var1
and a.m_var2 = b.m_var2
and ...
/*Optional threshold-based matches*/
where a.o_var1 = b.o_var1
+ a.o_var2 = b.o_var2
+ ...
>= &MATCH_THRESHOLD;
quit;
Going further - if you have inconsistently entered data, you could use soundex or edit distance matching rather than exact matching for the optional conditions. If some optional matches are worth more than others, you can weight their contribution to the score.