Porter2 implements the english Porter2 stemmer. It is written completely using finite state machines to do suffix comparison, rather than the string-based or tree-based approaches. As a result, it is 660% faster compare to string comparison-based approach.
import "github.com/surgebase/porter2" fmt.Println(porter2.Stem("seaweed")) // should get seawe
This implementation has been successfully validated with the dataset from http://snowball.tartarus.org/algorithms/english/
This implementation by far has the highest performance of the various Go-based implementations, AFAICT. I tested a few of the implementations and the results are below.
To run the test again, you can run cmd/compare/compare.go (
go run compare.go).
Most of the implementations, like the ones in the table above, rely completely on suffix string comparison. Basically there's a list of suffixes, and the code will loop through the list to see if there's a match. Given most of the time you are looking for the longest match, so you order the list so the longest is the first one. So if you are luckly, the match will be early on the list. But regardless that's a huge performance hit.
This implementation is based completely on finite state machines to perform suffix comparison. You compare each chacter of the string starting at the last character going backwards. The state machines at each step will determine what the longest suffix is. You can think of the state machine as an unrolled tree.
However, writing large state machines can be very error-prone. So I wrote a quick tool to generate most of the state machines. The tool basically takes a file of suffixes, creates a tree, then unrolls the tree by dumping each of the nodes.
You can run the tool by
go run suffixfsm.go <filename>.
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