slowrake()
is written entirely in R, so it will probably
be slower than the Java version of RAKE that I plan on writing in the
near future (see the rapidraker
R package for updates). You
can speed up slowrake()
by ignoring the words’
part-of-speech (POS) when creating candidate keywords (i.e., set
stop_pos = NULL
).
slowrake()
is erroring from some memory issue
(OutOfMemoryError). How do I fix this?slowrake()
relies on Java for POS tagging. Your Java
virtual machine (JVM) may run out of memory during this process,
resulting in an OutOfMemoryError. To fix this, try giving Java
more memory:
To quote from XLConnect:
[java.parameters] are evaluated exactly once per R session when the JVM is initialized - this is usually once you load the first package that uses Java support, so you should do this as early as possible.
Also note that:
The upper limit of the
Xmx
parameter is system dependent - most prominently, 32bit Windows will fail to work with anything much larger than 1500m, and it is usually a bad idea to setXmx
larger than your physical memory size because garbage collection and virtual memory do not play well together.
If changing java.parameters
doesn’t help, you can always
tell slowrake()
to skip POS tagging by setting
stop_pos
to NULL
.
Each keyword’s score is found by summing up all of the scores assigned to its member words. For example, the score for the keyword “dog leash” is found by adding the score for the word “dog” with the score for the word “leash.”
slowrake()
appears to be incorrect. What can I do about
this?First, confirm that the tagging function used by
slowrake()
(get_pos_tags()
) is indeed giving
the wrong tags. To do that, try something like:
slowraker:::get_pos_tags(txt = "here is some text that I want tagged.")
.
If the returned tags are indeed incorrect, try using a different tagger
than the one used by slowrake()
. Note,
get_pos_tags()
is basically a wrapper around the POS
tagging functions found in the openNLP
and NLP
packages, so you’ll want to look outside those libraries for a different
tagger.