Recognizing synonyms in left_join in R - r

Question

I have several quite large data tables containing characters, which I would like to join with the entries in my database. The spelling is often not quite right, thus joining is not possible.
I know there is no way around creating a synonym table to replace some misspelled characters. But is there a way to automatically detect certain anomalies (see example below)?
My data tables look similar to this:
data <- data.table(products=c("potatoe Chips", "potato Chips", "potato chips", "Potato-chips", "apple", "Apple", "Appl", "Apple Gala"))
The characters in my database are similar to this:
characters.database <- data.table(products=c("Potato Chips", "Potato Chips Paprika", "Apple"), ID=c("1", "2", "3"))
Currently if i perform a left_join only "Apple" will join:
data <- data %>%
left_join(characters.database, by = c('products'))
Result:
products
ID
potatoe Chips
NA
potato Chips
NA
potato chips
NA
Potato-chips
NA
apple
NA
Apple
3
Appl
NA
Apple Gala
NA
Is it possible to automatically ignore: "Case letters", space" ", "-", and an "e" at the end of a word during left_join?
This would be the table i would like:
products
ID
potatoe Chips
1
potatoChips
1
potato chips
1
Potato-chips
1
apple
1
Apple
3
Appl
1
Apple Gala
NA
Any Ideas?

Answer 1

If I were you, I'd do a few things:
I'd strip all special characters, lower case all characters, remove spaces, etc. That'd help a bunch (i.e. potato chips, Potato Chips, and Potato-chips all go to "potatochips" which you can then join on).
There's a package called fuzzyjoin that will let you join on regular expressions, by edit distance, etc. That'll help with Apple vs Apple Gala and misspellings, etc.
You can strip special characters (only keep letters) + lowercase with something like:
library(stringr)
library(magrittr)
string %>%
str_remove_all("[^A-Za-z]+") %>%
tolower()

Answer 2

Thanks Matt Kaye for your suggestion I did something similar now.
As I need the correct spelling in the data base and some of my characters contain symbols and numbers which are relevant I did the following:
#data
data <- data.table(products=c("potatoe Chips", "potato Chips", "potato chips", "Potato-chips", "apple", "Apple", "Appl", "Apple Gala"))
characters.database <- data.table(products=c("Potato Chips", "Potato Chips Paprika", "Apple"), ID=c("1", "2", "3"))
#remove spaces and capital letters in data
data <- data %>%
mutate(products= tolower(products)) %>%
mutate(products= gsub(" ", "", products))
#add ID to database
characters.database <- characters.database %>%
dplyr::mutate(ID = row_number())
#remove spaces and capital letters in databasr product names
characters.database_syn <- characters.database %>%
mutate(products= tolower(products)) %>%
mutate(products= gsub(" ", "", products))
#join and add correct spelling from database
data <- data %>%
left_join(characters.database_syn, by = c('products')) %>%
select(product_syn=products, 'ID') %>%
left_join(characters.database, by = c('ID'))
#other synonyms have to manually be corrected or with the help of a synonym table (As in MY data special caracters are relevant!)