1720196450

Aspects of developing a children's book recommendation system


In this post we're going to solve some common challenges encountered by programmers when building recommendation systems. We'll use python and javascript in this example, but feel free to solve them in the comments using your favorite language. To begin with, we'll create a script to collect data on children's books, including title, author, recommended age, genre and reader ratings. Python ```py import requests import json def collect_book_data(api_url): response = requests.get(api_url) if response.status_code == 200: books = response.json() with open('books.json', 'w') as file: json.dump(books, file) print("Book data saved successfully.") else: print("Failed to collect data.") api_url = "https://api.example.com/children_books" collect_book_data(api_url) ``` Javascript ```js const fetch = require('node-fetch'); const fs = require('fs'); async function collectBookData(apiUrl) { try { const response = await fetch(apiUrl); const books = await response.json(); fs.writeFileSync('books.json', JSON.stringify(books, null, 2)); console.log("Book data saved successfully."); } catch (error) { console.error("Failed to collect data.", error); } } const apiUrl = "https://api.example.com/children_books"; collectBookData(apiUrl); ``` Next we'll implement an algorithm to filter out books suitable for a certain age group. python ```py import json def filter_books_by_age(age): with open('books.json', 'r') as file: books = json.load(file) suitable_books = [book for book in books if book['age_recommended'] == age] return suitable_books age = 7 books_for_age = filter_books_by_age(age) print(books_for_age) ``` javascript ```js const fs = require('fs'); function filterBooksByAge(age) { const books = JSON.parse(fs.readFileSync('books.json')); return books.filter(book => book.age_recommended === age); } const age = 7; const booksForAge = filterBooksByAge(age); console.log(booksForAge); ``` The next step is to develop the recommendation algorithm based on children's interests python ```py def recommend_books(interest, age): with open('books.json', 'r') as file: books = json.load(file) recommendations = [book for book in books if interest in book['genres'] and book['age_recommended'] == age] return recommendations interest = 'adventure' age = 7 recommended_books = recommend_books(interest, age) print(recommended_books) ``` javascript ```js function recommendBooks(interest, age) { const books = JSON.parse(fs.readFileSync('books.json')); return books.filter(book => book.genres.includes(interest) && book.age_recommended === age); } const interest = 'adventure'; const age = 7; const recommendedBooks = recommendBooks(interest, age); console.log(recommendedBooks); ``` And finally, we've added a feature to allow users to rate books and see recommendations based on those ratings. python ```py def rate_book(book_id, rating): with open('books.json', 'r') as file: books = json.load(file) for book in books: if book['id'] == book_id: if 'ratings' not in book: book['ratings'] = [] book['ratings'].append(rating) break with open('books.json', 'w') as file: json.dump(books, file) book_id = 1 rating = 5 rate_book(book_id, rating) ``` javascript ```js function rateBook(bookId, rating) { const books = JSON.parse(fs.readFileSync('books.json')); const book = books.find(b => b.id === bookId); if (book) { book.ratings = book.ratings || []; book.ratings.push(rating); } fs.writeFileSync('books.json', JSON.stringify(books, null, 2)); } const bookId = 1; const rating = 5; rateBook(bookId, rating); ``` This post covers different aspects of developing a children's book recommendation system, from data collection to personalized recommendation and book evaluation. Don't forget to join our community to help our work reach more people interested in learning, teaching and sharing programming content.

(0) Comments