May 2018
Intermediate to advanced
228 pages
4h 11m
Japanese
Content preview from Rによるテキストマイニング ―tidytextを活用したデータ分析と可視化の基礎
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82
■
5
章 未整理形式へ（から）の変換
スタディにつないでいきます。
コーパス
オブジェクト
コーパス
オブジェクト
テキスト
集計データ
テキスト
データ
可視化
整理テキスト
センチメント
辞書
DTM
コーパス
オブジェクト
unnest_tokens
tidytext
count
dplyr
ggplot2
inner_join
dplyr
tm
quanteda
tidy
tidytext
tm,
quanteda
cast_dtm
cast_dfm
tidytext
tidy
tidytext
dplyr, tidyr
tm, quanteda
group_by
summarize
dplyr
dplyr, tidyr
図5-1 tidytextとその他のツール、データ形式（特にtm、quantedaパッケージ）を併用する
典型的なテキスト分析のフローチャート。この章は、DTMと整理データフレームの
相互変換とコーパスオブジェクトの整理データフレームへの変換の方法を説明する。
5.1
DTM
の整理
DTM
（文書
-
単語行列、
https://en.wikipedia.org/wiki/Document-term_mat
rix
）は、
テキストマイニングパッケージの操作対象として最も広く使われているデータ構造
の
1
つで、次のような特徴を持っています。
●
各行は、
1
つの文書（本や章）を表します。
●
各列は、
1
つの単語を表します。
●
個々の値は、（一般に）その単語の文書内における出現頻度です。
文書と単語のほとんどの組み合わせは出現回数なし（値
0
）
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.