I have a large collection of strings that each contain information about a certain product. For example:
wine Bardolo red 1L 12b 12% La Tulipe, 13* box 3 bottles, 2005 Great Johnny Walker 7CL 22% red label Wisky Jonny Walken .7 Red limited editon The number of product names is limited, as are most other properties, but they might be misspelled. I would like to extract keywords from all those strings. Product name, product type, volume, etc. But I'm not sure what the best approach would be and if ElasticSearch would be the tool of choice. I've looked at PostgreSQL's trigram plugin (pg_tgrm) since all data sits in a PostgreSQL db at the moment, but that seems limited. I was thinking about creating some kind of master list of proper keyword and try to match words from a string with those keywords. These words could be misspelled meaning they would have to be: 1. fuzzy matched 2. matched by hand 3. match by some sort of neural network trained with existing data Someone suggested "analyzing the entire string as an ngram using the ngram tokenizer", but I'm not sure. Any pointers where I should direct my effort would be highly appreciated! -- You received this message because you are subscribed to the Google Groups "elasticsearch" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/ebe7e730-7488-425e-af77-975d5679d0dc%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
