Enhancing Personalized Recommendations: A Spacy-Based Hybrid Approach for Book Recommendation Systems

• Author(s): Jayank Tyagi ; Vandana Choudhary ; Namita Goyal
• Paper ID: 1704684
• Page: 550-557
• Published Date: 18-06-2023
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 12 June-2023

Abstract

Recommendation systems have become ubiquitous in our digital age, with various platforms utilizing algorithms to predict what items users might be interested in and offer personalized recommendations. To build more effective recommendation models, it is essential to analyse and understand natural language, such as product descriptions or user reviews. Tokenization, part-of-speech tagging, named entity recognition, dependency parsing, and other features offered by Spacy, an open-source NLP toolkit, are effective tools that may be used to extract meaning from natural language text. Using Spacy, it is possible to identify the key topics or themes of a product description or review and match them to the interests of individual users. Spacy's speed and scalability make it well-suited for real-time recommendation systems that need to process large volumes of data quickly. As such, Spacy has become increasingly popular among researchers and practitioners working in this area, due to its unique set of NLP features and capabilities.

Citations

IRE Journals:
Jayank Tyagi , Vandana Choudhary , Namita Goyal "Enhancing Personalized Recommendations: A Spacy-Based Hybrid Approach for Book Recommendation Systems" Iconic Research And Engineering Journals Volume 6 Issue 12 2023 Page 550-557

IEEE:
Jayank Tyagi , Vandana Choudhary , Namita Goyal "Enhancing Personalized Recommendations: A Spacy-Based Hybrid Approach for Book Recommendation Systems" Iconic Research And Engineering Journals, 6(12)