Python uses spaCy to achieve text similarity calculation

To achieve text similarity calculation using spaCy, it is first necessary to build a Python environment and install the necessary class libraries. The following are the preparation steps: 1. Install Python: From the Python official website（ https://www.python.org/downloads/ ）Download and install the latest version of Python. 2. Install pip: Run 'Python - m securepip -- default pip' from the command line to install pip. 3. Install spaCy: Run 'pip install - U space' from the command line to install spaCy. 4. Download the pre trained model of spaCy: Run 'Python - m spacy download en' from the command line_ Core_ Web_ SM 'to download the English language model. This model can be used to process English text data. After the preparation work is completed, we can start using spaCy for text similarity calculation. In this example, we will use spaCy to calculate the similarity score between two texts. Firstly, we need to create a Python script file and import the necessary class libraries and models. python import spacy #Load pre trained English language model nlp = spacy.load('en_core_web_sm') Then, we need to create a function to calculate the similarity score between two texts. python def calculate_similarity(text1, text2): #Build two texts as spaCy document objects doc1 = nlp(text1) doc2 = nlp(text2) #Calculate text similarity similarity_score = doc1.similarity(doc2) return similarity_score Now we can use this function to calculate the similarity between two texts. The following is an example of usage: python text1 = "I love apples" text2 = "I like bananas" similarity_score = calculate_similarity(text1, text2) print(f"Similarity score: {similarity_score}") This will output the similarity score between two texts. The complete source code is as follows: python import spacy #Load pre trained English language model nlp = spacy.load('en_core_web_sm') def calculate_similarity(text1, text2): #Build two texts as spaCy document objects doc1 = nlp(text1) doc2 = nlp(text2) #Calculate text similarity similarity_score = doc1.similarity(doc2) return similarity_score text1 = "I love apples" text2 = "I like bananas" similarity_score = calculate_similarity(text1, text2) print(f"Similarity score: {similarity_score}") This sample code can calculate the similarity score between two texts, and you can modify the text content according to your own needs.