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:
options(java.parameters = "-Xmx1024m")
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.