How to perform approximate (fuzzy) name matching in R

Question

I have a large data set, dedicated to biological journals, which was being composed for a long time by different people. So, the data are not in a single format. For example, in

Answer 1

There are packages that can help you with this, and some are listed in the comments. But, if you don't want to use these, I though I'd try to write something in R that might help you. The code will match "John Smith" with "J Smith", "John Smith", "Smith John", "John S". Meanwhile, it won't match something like "John Sally".

# generate some random names
names = c(
  "John Smith", 
  "Wigberht Ernust",
  "Samir Henning",
  "Everette Arron",
  "Erik Conor",
  "Smith J",
  "Smith John",
  "John S",
  "John Sally"
);

# split those names and get all ways to write that name
split_names = lapply(
  X = names,
  FUN = function(x){
    print(x);
    # split by a space
    c_split = unlist(x = strsplit(x = x, split = " "));
    # get both combinations of c_split to compensate for order
    c_splits = list(c_split, rev(x = c_split));
    # return c_splits
    c_splits;
  }
)

# suppose we're looking for John Smith
search_for = "John Smith";

# split it by " " and then find all ways to write that name
search_for_split = unlist(x = strsplit(x = x, split = " "));
search_for_split = list(search_for_split, rev(x = search_for_split));

# initialise a vector containing if search_for was matched in names
match_statuses = c();

# for each name that's been split
for(i in 1:length(x = names)){

  # the match status for the current name
  match_status = FALSE;

  # the current split name
  c_split_name = split_names[[i]];

  # for each element in search_for_split
  for(j in 1:length(x = search_for_split)){

    # the current combination of name
    c_search_for_split_names = search_for_split[[j]];

    # for each element in c_split_name
    for(k in 1:length(x = c_split_name)){

      # the current combination of current split name
      c_c_split_name = c_split_name[[k]];

      # if there's a match, or the length of grep (a pattern finding function is
      # greater than zero)
      if(
        # is c_search_for_split_names first element in c_c_split_name first
        # element
        length(
          x = grep(
            pattern = c_search_for_split_names[1],
            x = c_c_split_name[1]
          )
        ) > 0 &&
        # is c_search_for_split_names second element in c_c_split_name second 
        # element
        length(
          x = grep(
            pattern = c_search_for_split_names[2],
            x = c_c_split_name[2]
          )
        ) > 0 ||
        # or, is c_c_split_name first element in c_search_for_split_names first 
        # element
        length(
          x = grep(
            pattern = c_c_split_name[1],
            x = c_search_for_split_names[1]
          )
        ) > 0 &&
        # is c_c_split_name second element in c_search_for_split_names second 
        # element
        length(
          x = grep(
            pattern = c_c_split_name[2],
            x = c_search_for_split_names[2]
          )
        ) > 0
      ){
        # if this is the case, update match status to TRUE
        match_status = TRUE;
      } else {
        # otherwise, don't update match status
      }
    }
  }

  # append match_status to the match_statuses list
  match_statuses = c(match_statuses, match_status);
}

search_for;

[1] "John Smith"

cbind(names, match_statuses);

     names             match_statuses
[1,] "John Smith"      "TRUE"        
[2,] "Wigberht Ernust" "FALSE"       
[3,] "Samir Henning"   "FALSE"       
[4,] "Everette Arron"  "FALSE"       
[5,] "Erik Conor"      "FALSE"       
[6,] "Smith J"         "TRUE"        
[7,] "Smith John"      "TRUE"        
[8,] "John S"          "TRUE"
[9,] "John Sally"      "FALSE"   

Hopefully this code can serve as a starting point, and you may wish to adjust it to work with names of arbitrary length.

Some notes:

• for loops in R can be slow. If you're working with lots of names, look into Rcpp.

• You may wish to wrap this in a function. Then, you can apply this for different names by adjusting search_for.

• There are time complexity issues with this example, and depending on the size of your data, you may want/need to rework it.