Open Dataset
Data Structure ?
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Data Structure ?
*The above analysis is the result extracted and analyzed by the system, and the specific actual data shall prevail.
README.md
コンテキスト
ようこそ。これは、顧客が書いたレビューを中心とした女性服の電子商取引データセットです。9つの補助的な特徴量により、複数の次元からテキストを解析するための良好な環境が提供されます。これは実際の商業データであるため、匿名化されており、レビューテキストや本文中の会社への言及は「小売業者」に置き換えられています。
内容
このデータセットには23486行と10個の特徴変数が含まれています。各行は顧客のレビューに対応しており、以下の変数が含まれています。
- **衣類ID**:レビュー対象の特定の商品を指す整数のカテゴリ変数。
- **年齢**:レビュー投稿者の年齢を表す正の整数変数。
- **タイトル**:レビューのタイトルを表す文字列変数。
- **レビュー本文**:レビューの本文を表す文字列変数。
- **評価**:顧客が付与した商品の評価点数を表す正の順序尺度の整数変数。1が最悪、5が最高。
- **推薦有無**:顧客が商品を推薦するかどうかを示す二値変数。1は推薦、0は非推薦。
- **肯定的なフィードバック数**:このレビューを肯定的だと感じた他の顧客の数を記録した正の整数。
- **大分類名**:商品の大分類のカテゴリ名。
- **部門名**:商品の部門のカテゴリ名。
- **クラス名**:商品のクラスのカテゴリ名。
謝辞
匿名ですが、実際の出典
インスピレーション
質の高い自然言語処理を期待しています!特徴量エンジニアリングや多変量解析にも素敵な機会があります。
出版物
[双方向再帰型ニューラルネットワークを用いた感情分類による電子商取引レビューの統計的分析](https://www.researchgate.net/publication/323545316_Statistical_Analysis_on_E-Commerce_Reviews_with_Sentiment_Classification_using_Bidirectional_Recurrent_Neural_Network)
著者:[アビエン・フレッド・アガラップ](https://www.kaggle.com/afagarap) - [Github](https://github.com/AFAgarap/ecommerce-reviews-analysis)
著者:[アビエン・フレッド・アガラップ](https://www.kaggle.com/afagarap) - [Github](https://github.com/AFAgarap/ecommerce-reviews-analysis)
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