阅读分享：Enriching BERT with Knowledge Graph Embeddings for Document Classification

Enriching BERT with Knowledge Graph Embeddings for Document Classification

• https://github.com/malteos/pytorch-bert-document-classification

子任务A：对一本书进行八分类；
子任务B：第二层93个和第三层242个标签(总共343个标签)进行分类。

Arthitecture：

• Title
• Text：A short descriptive text (blurb) with an average length of 95 words.
• Metadata：
  • Number of authors.
  • Academic title (Dr. or Prof.), if found in author names (0 or 1).
  • Number of words in title.
  • Number of words in blurb.
  • Length of longest word in blurb.
  • Mean word length in blurb.
  • Median word length in blurb.
  • Age in years after publication date.
  • Probability of