自然语言处理（八）：Lexical Semantics

目录

1. Sentiment Analysis

2. Lexical Database

2.1 What is Lexical Database

2.2 Definitions

2.3 Meaning Through Dictionary

2.4 WordNet

2.5 Synsets

2.6 Hypernymy Chain

3. Word Similarity

3.1 Word Similarity with Paths

3.2 超越路径长度

3.3 Abstract Nodes

3.4 Concept Probability Of A Node

3.5 Similarity with Information Content

4. Word Sense Disambiguation

4.1 Word Sense Disambiguation

4.2 Supervised WSD 有监督词义消歧

4.3 Unsupervised: Lesk 无监督：Lesk

4.4 Final Words

---

1. Sentiment Analysis

Bag of words, kNN classifier. Training data 词袋模型，kNN分类器。训练数据:

• “This is a good movie.” → ☺
• “This is a great movie.” → ☺
• “This is a terrible film.” → ☹
• “This is a wonderful film.” → ?

Two problems：

• The model does not know that "movie" and "film' are synonyms. Since "film" appears only in negative examples the model learns that it is a negative word. 模型不知道“电影”和“影片”是同义词。因为“影片”只出现在负面例子中，所以模型认为它是一个负面词。
• "wonderful" is not in the vocabulary (OOV ---- Out-Of-Vocabulary). “wonderful”不在词汇表里

Comparing words directly will not work. How to make sure we compare word meanings instead?

Solution: add this information explicitly through a lexical database. 通过 lexical database 显式添加此信息。

2. Lexical Database

2.1 What is Lexical Database

Their dictionary definition 

• But dlictionary definitions are necessarily circular
• Only useful if meaning is already understood

Their relationships with other words

• Also circular, but better for text analysis

2.2 Definitions

A word sense describes one aspect of the meaning of a word 词义描述了一个词的意义的一个方面

If a word has multiple senses, it is polysemous 如果一个词有多个义项，它就是多义词

2.3 Meaning Through Dictionary

Gloss: textual definition of a sense, given by a dictionary

Bank

• financial institution that accepts deposits and channels the money into lending activities
• sloping land (especially the slope beside a body of water)

Another way to define meaning: by looking