What I have is a database of fields, and a collection of strings, that are comprised of those fields with some level of distortion. I need to match those things, to the entries in the database
Example:
- Animal: Bear
- Fur: Brown
- Weight: 544 kg
- Location: Alaska
- Name: Greg
- Hat: Fanciful
And then a string that basically takes some of those fields at random and then distorts them, runs them together and may add trash data to the string. Some examples of how these could be distorted:
- BrowBear 544 #982385 Alsk
- ALASALASKA GregFanciful BeaBear
There may be strings that follow the same pattern of distortion, and there may not be.
My task is to match the distorted strings, to their respective entries in the database.
I’m not looking for an answer, but rather some directions to go. Most of my interest up until this point has focused on things like Neural Nets, CLA/ HTM, Bayesian Networks, Deep Learning, Neo4j, you kind of see the pattern, I like things involving networks of information, or anything that tries to model the human brain.
But I’m not so sure those models would work well here.
I’m not looking for an answer, just a direction to head in. If you had to solve this problem, how would you encapsulate all of the possibilities? I have an elastic search cluster set up and I’m currently using it to create a trained data set, mapping the strings to their entries in the database.
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