主题建模测验

当您参加测验时，就会出现答案和解释。

1. 在LDA公式中，如何用词汇表表示模型主题？
   • 仅作为一个强制性人类编写的关键词
   • 作为词的概率分布
   • 作为每个句子的语法解析
   • 作为没有词汇表表示的情感值
2. Why can an unsupervised LDA topic model be fit to documents without topic labels?
   • It requires a verified category for every document first
   • It reads only documents with identical titles
   • It necessarily uses a classifier trained on the same task labels
   • It infers unobserved topic structure from the observed words
3. LDA 如何处理单个文档？
   • 由于完全属于一个主题
   • 作为词序至关重要的序列
   • 作为多个主题不同比例的混合体
   • 作为要扫描的文本图像
4. 经典 LDA 使用的“词袋”假设是什么？
   • 它忽略词序并仅使用字数统计
   • 它只保留每个文档的第一句
   • 它首先将每个文档翻译成英文
   • 它要求单词按字母顺序排列
5. 在运行 LDA 之前您通常必须做出哪个决定？
   • 每个主题的确切标题
   • 每个文档的作者
   • 文档书写的字体
   • 要查找的主题数 K
6. Which stage commonly starts BERTopic's grouping of documents rather than relying only on raw word counts?
   • Assigning every document a manually required topic label
   • Clustering representations derived from document embeddings
   • Removing all text before computing any representation
   • Treating every document as an identical image file
7. When inspecting LDA's high-probability words, who can supply a descriptive topic name such as election coverage?
   • An analyst interpreting the weighted words and documents
   • A probability value that necessarily proves one official name
   • A required government approver for every model run
   • A document filename that always determines the meaning
8. After BERTopic groups documents, what does c-TF-IDF help produce for each cluster?
   • The original input image pixels
   • A required dependency parse for every token
   • Characteristic weighted words representing the group
   • Proof that every cluster has exactly one true theme