Dear R users,


Suppose I have a data set with inconsistent names for a field.

I desire to make these to consistent names.

i.e

"University of New Jersey", "New Jersey Uni", "New Jersey University" (3
different inconsistent names) to "The University of New Jersey" (consistent
name)

Below are arbitrary data set produced from "state.name" (built in data set
in R) and associated scripts.


d <- as.data.frame(c(state.name[30:40], paste(state.name[30:40],
"University", sep=" "), paste("Th University of", state.name[30:40], sep="
"),paste("University o", state.name[30:40], sep=" ")))
da <- sapply(d, as.character)   # factor to character transformation

spl <- strsplit(da, " ")   # spliting components

dd <- character(dim(da)[1])   # initializing empty vector
for (i in 1:dim(da)[1])   {
    if (sum(c("New", "Jersey", "University") %in% spl[[i]]) >= 3)
dd[i] <- "The University of New Jersey"
     else if (sum(c("New", "Mexico", "University") %in% spl[[i]]) >= 3)
dd[i] <- "The University of New Mexico"
     else if (sum(c("New", "York") %in% spl[[i]]) >=
2)                         dd[i] <- "The University of New York"
     else if (sum(c("North", "Carolina") %in% spl[[i]]) >=
2)                   dd[i] <- "The university of North Carolina"
}

Note: above shows only partial (if/else if) conditions.

Q1: The above "for" loop works fine (but very slow on large data set..),
thus I would like to explore whether there is an alternative VECTORIZATION
method that may speed up the process.


Q2: Also, is there other way to extract a string from a phrase without using
"%in%"?

i.e
> "ac" %in% unlist(strsplit("ac dc", " "))
[1] TRUE

Your expertise in resolving this problem would be greatly appreciated.


Steven Kang

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