Program 5
Aim:
Use word embeddings to create meaningful sentences for
creative tasks. Retrieve similar words for a seed word. Create a sentence or
story using these words as a starting point. Write a program that:
Takes a seed word. Generates similar words.
Constructs a short paragraph using these words.
Theory:
Creative Sentence Generation using Word
Embeddings
Word embeddings are a technique in Natural Language
Processing (NLP) used to represent words as numerical vectors based on their
meanings and relationships. Words that have similar meanings are placed closer
together in the vector space. Common models include Word2Vec and GloVe.
In this experiment, word embeddings are used to
perform a creative text generation task. A seed word is given as input, and the
embedding model is used to retrieve a set of similar words based on semantic
similarity. These similar words act as a foundation for generating meaningful
sentences or a short paragraph.
The generated words are then combined to construct a
coherent sentence or story, demonstrating how semantic relationships between
words can be used for creative writing tasks. This approach helps in improving
vocabulary usage and generating contextually relevant text.
Program
Step1: Creative Sentence Generation using
Word Embeddings
Step 2:
Result: Similar Words and Generated
Paragraph
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