Using Word2Vec

Jane is a content manager for an e-commerce website that sells a wide variety of products. Her role involves categorizing and organizing product descriptions, ensuring accurate search results, and providing personalized recommendations to customers. However, Jane faces a challenge in understanding the underlying relationships and similarities between different products based on their descriptions alone. Jane presents the challenges to the website’s data scientist, Emma. Emma understands that the goals are to identify common product-related issues and relationships between different products, and discover potential areas for new products. Emma decides to use Word2Vec, a popular word embedding technique, to convert words to vectors. Word2Vec will enable Emma to measure the similarity between words, allowing search engines to return more relevant results. This is certainly an appealing feature for the e-commerce website. Word2Vec-derived embeddings can enhance document...