Abstract:
roday how much data the web develops quickly and individuals need a few
instruments to find and access suitable data. One of such techniques is known as a
recommendation system. Recommendation systems help to explore rapidly and get
fundamental data. For the most part they are utilised in Internet shops to expand the
benefit. This teporl explores different techniques used for the recommendation of a
on
book. Different stages involve signup & sign in for buying books, reading books,
payment option is included and by the liking ofthe user this system suggests the books.
The final product will use php for frontend and backend and python for recommending
books.
This project uses the Artificial Neural Network technique to develop the software. The
main advantage of using this recommendation system is to make it easier to find a
good book to teach his/her students as we know that there are a lot of books over the
internet and sometimes readers cannot choose which book is more suitable for him or
for his/her students.
We use Python to calculate a numeric value that denotes the similarity between two
books. Cosine Similarity is a function that returns the 20 most similar books based on
the cosine similarity score.
The application is user friendly and is very beneficial for readers. Our main aim to
reduce time offinding appropriate book in respective field.
