Hi,
Not sure exactly what you need but looks interesting.
Something a bit like this ?
DT[ word == "good", .SD[ lag(word, N) != "not" ], by=document]
Your idea being you don't want to have to repeat all the pre and post
words alongside each word but rather express it in the query. Makes
sense. Leads to classifying "not good" and "not very good" as both
negative phrases I guess.
Matt
On 26/06/14 21:56, Matthew DeAngelis wrote:
Hello data.table gurus,
I have been using data.table to efficiently work with textual data and
I love it for that purpose. I have transformed my data so that it
looks something like this:
word document position
I 1 1
have 1 2
transformed 1 3
my 1 4
data 1 5
so 2 1
that 2 2
it 2 3
looks 2 4
something 2 5
like 2 6
this 2 7
(I actually use a unique number for each word, so that I am able to
use data.table's excellent features to do lightning-fast word counts.
This has revolutionized my workflow over looping through text files
with Perl.)
My problem is that I sometimes need to search for phrases or to select
words based on their context (for instance, I may want to exclude a
word if it is preceded by "not" or followed by a word that changes its
meaning). Currently, I am using the solution here
<http://stackoverflow.com/questions/11397771/r-data-table-grouping-for-lagged-regression> to
create a new column for a word in another position, like this:
word document position lead_word
I 1 1 have
have 1 2 transformed
transformed 1 3 my
my 1 4 data
data 1 5 NA
so 2 1 that
that 2 2 it
it 2 3 looks
looks 2 4 something
something 2 5 like
like 2 6 this
this 2 7 NA
using a command like: DT[,lead_word:=DT[list(document,position+1),word].
This approach has two problems, however. First, it consumes more
resources as the dataset grows. I am currently working with a file
containing over 150 million rows, so adding a column is costly.
Second, I may want to check both one and two words ahead, so that I
have to add two columns, and this can quickly get out of hand.
Is there a better way to use data.table to check the value in a row N
distance from the row of interest within a group and select a row
based on that value? Perhaps the .I variable could be useful here?
I appreciate any suggestions.
Regards,
Matt
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