Similar words in a vocabulary
Finding semantically similar terms has various applications in information retrieval. In this exercise, you will practice finding the most semantically similar term to the word computer from the en_core_web_md model's vocabulary.
The computer word vector is already extracted and stored as word_vector. The en_core_web_md model is already loaded as nlp, and NumPy package is loaded as np.
You can use the .most_similar() function of the nlp.vocab.vectors object to find the most semantically similar terms. Using [0][0] to index the output of this function will return the word IDs of the semantically similar terms. nlp.vocab.strings[<a given word>] can be used to find the word ID of a given word and it can similarly return the word associated with a given word ID.
Cet exercice fait partie du cours
Natural Language Processing with spaCy
Instructions
- Find the most semantically similar term from the
en_core_web_mdvocabulary. - Find the list of similar words given the word IDs of the similar terms.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Find the most similar word to the word computer
most_similar_words = nlp.vocab.vectors.____(np.asarray([____]), n = 1)
# Find the list of similar words given the word IDs
words = [nlp.____.____[____] for w in most_similar_words[0][0]]
print(words)