amenable in Constant 2016
of words" is used to underscore how in the
course of processing a text the original order of the words in sentence form is stripped away.
The resulting representation is then a collection of each unique word used in the text,
typically weighted by the number of times the word occurs.
Bag of words, also known as word histograms or weighted term vectors, are a standard part
of the data engineer's toolkit. But why such a drastic transformation? The utility of "bag of
words" is in how it makes text amenable to code, first in that it's very straightforward to
implement the translation from a text document to a bag of words representation. More
P.66
P.67
significantly, this transformation then opens up a wide collection of tools and techniques for
further transformation and analysis purposes. For instance, a number of libraries available in
the booming field of "data sciences" work with "high dimension" vectors; bag of words is a
way to transform a written document into a mathematical vector wher
rds. While "bag of words" might well serve as a
cautionary reminder to programmers of the essential violence perpetrated to a text and a call
to critically question the efficacy of methods based on subsequent transformations, the
expressions use seems in practice more like a badge of pride or a schoolyard taunt that would
go: Hey language: you're nothing but a big BAG-OF-WORDS. Following this spirit of the
term, "bag of words" celebrates a perfunctory step of "breaking" a text into a purer form
amenable to computation, to stripping language of its silly redundant repetitions and foolishly
contrived stylistic phrasings to reveal a purer inner essence.
BOOK OF WORDS
Lieber's Standard Telegraphic Code, first published in 1896 and republished in various
updated editions through the early 1900s, is an example of one of several competing systems
of telegraph code books. The idea was for both senders and receivers of telegraph messages
to use the books to translate their messages into a sequence of c
amenable in Murtaugh 2016
f words" is used
to underscore how in the course of processing a text the original order of the
words in sentence form is stripped away. The resulting representation is then
a collection of each unique word used in the text, typically weighted by the
number of times the word occurs.
Bag of words, also known as word histograms or weighted term vectors, are a
standard part of the data engineer's toolkit. But why such a drastic
transformation? The utility of "bag of words" is in how it makes text amenable
to code, first in that it's very straightforward to implement the translation
from a text document to a bag of words representation. More significantly,
this transformation then opens up a wide collection of tools and techniques
for further transformation and analysis purposes. For instance, a number of
libraries available in the booming field of "data sciences" work with "high
dimension" vectors; bag of words is a way to transform a written document into
a mathematical vector where each "dimens
rds. While "bag of words" might well serve as a
cautionary reminder to programmers of the essential violence perpetrated to a
text and a call to critically question the efficacy of methods based on
subsequent transformations, the expressions use seems in practice more like a
badge of pride or a schoolyard taunt that would go: Hey language: you're
nothing but a big BAG-OF-WORDS. Following this spirit of the term, "bag of
words" celebrates a perfunctory step of "breaking" a text into a purer form
amenable to computation, to stripping language of its silly redundant
repetitions and foolishly contrived stylistic phrasings to reveal a purer
inner essence.
## Book of words
Lieber's Standard Telegraphic Code, first published in 1896 and republished in
various updated editions through the early 1900s, is an example of one of
several competing systems of telegraph code books. The idea was for both
senders and receivers of telegraph messages to use the books to translate
their messages into a sequence
Display 200 300 400 500 600 700 800 900 1000 ALL characters around the word.