Python uses NLTK to implement word segmentation: dividing a paragraph of text into separate words

Implementing word segmentation using NLTK (Natural Language Toolkit) in Python requires some preparation work: 1. Install NLTK library: You can use the 'pip install nltk' command to install the NLTK library. 2. Download the required datasets for NLTK: NLTK provides multiple datasets, including datasets for word segmentation. Before using the word segmentation function, we need to download one of the datasets. python import nltk nltk.download('punkt') This will download the word segmentation dataset named 'punkt'. After the preparation work is completed, we can use NLTK's' word '_ The tokenize 'method implements word segmentation. Sample data: We will use a paragraph of text as the sample data. python text = "Natural Language Processing (NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and humans using natural language." Now we can write complete code to implement word segmentation and print out the results. python import nltk from nltk.tokenize import word_tokenize #Download word segmentation dataset nltk.download('punkt') #Enter text text = "Natural Language Processing (NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and humans using natural language." #Participle tokens = word_tokenize(text) #Print segmentation results print(tokens) Output results: ['Natural', 'Language', 'Processing', '(', 'NLP', ')', 'is', 'a', 'subfield', 'of', 'artificial', 'intelligence', 'that', 'focuses', 'on', 'the', 'interaction', 'between', 'computers', 'and', 'humans', 'using', 'natural', 'language', '.'] The above code provides a detailed introduction to the complete process of using NLTK to implement word segmentation in Python.