Comments (2)
Hey @acoroleu-tempus, thanks for trying out the library. I noticed some similar and some different behavior to what you described.
- I've used it for typically ~200 contacts (constructor takes <1s), maybe <1000 contacts. I tried it with 10k and it took 55s, so similar to you
- The
EnContactMatcher
is a fairly opinionated matcher. It has anAcceleratedFuzzyMatcher
that uses theEnHybridDistance
for both the contact's names and aliases that is processed with theWhitespaceTokenizer
andEnPreProcessor
that does a kind of a windowing on the name to add variations. So if you'd like to deviate from it you should have all the components to build a matcher to do what you want to do. - constructor time I agree with, switching from the internal
AcceleratedFuzzyMatcher
toFuzzyMatcher
(55s->25s similar to you). Butfind
time was fairly drastic (10ms to 192ms), a ~2x start cost for a ~19x query reduction gain. the "0.1 seconds with accelerated" seems a bit high in your case? If we were talking about a smaller number of contacts, like 200 instead of 10k, the comparison is a lot closer (425ms build 2ms find vs 301ms build 4ms find, respectively)
Because of a noticeable difference in (3), and how the performance gap gets bigger with more contacts and how EnContactMatcher
may expand the contact list from the original size with the windowing it does (thus a bigger contact list), I do not recommend (2).
from phoneticmatching.
Hi @Mmdixon, the current preprocessing of EnContactMatcher
looks what we need in order to increase accuracy results.
Would it be possible to make FuzzyMatcher
serializable? Given the constructor takes some time, when being passed a large number of contacts, we'd like to serialize and store in Redis so it can be re-used (deserialized).
Thanks for your support!
from phoneticmatching.
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