E-commerce website with integrated recommendation system
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This abstract presents the development of an e-commerce web application using Django framework, incorporating the TF-IDF vectorization technique and cosine similarity for efficient search functionality. The web application aims to provide users with a seamless and intuitive shopping experience. The Django framework offers a robust and scalable platform for building web applications. It provides a high level of abstraction, allowing developers to focus on the application logic rather than low-level details. By utilizing Django, the e-commerce application benefits from features like URL routing,...
This abstract presents the development of an e-commerce web application using Django framework, incorporating the TF-IDF vectorization technique and cosine similarity for efficient search functionality. The web application aims to provide users with a seamless and intuitive shopping experience. The Django framework offers a robust and scalable platform for building web applications. It provides a high level of abstraction, allowing developers to focus on the application logic rather than low-level details. By utilizing Django, the e-commerce application benefits from features like URL routing, database management, and user authentication. For the search functionality, the application employs TF-IDF (Term Frequency-Inverse Document Frequency) vectorization technique. TF-IDF calculates the importance of a term in a document by considering its frequency within the document and its rarity in the overall corpus. This technique allows for efficient representation of textual data, enabling quick and accurate search results.
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