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Libraries, big or small, can accumulate thousands of books in their collection. Managing such a vast collection and making appropriate recommendations can quickly become a time-consuming task especially without the assistance of technology. Fortunately, SQL (Structured Query Language) is built to handle such large datasets and do all the heavy lifting for us. It is time to explore how we can leverage SQL’s capabilities to develop a recommendation system for a library.
Getting Started: Setting Up The Database
The first step in creating our recommendation system is to set up a proper database to maintain our collection. The database will have the following tables: Books (containing info about the books), Readers (containing info about the readers), and BorrowedBooks (tracking the history of borrowed books).
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CREATE TABLE Books ( BookID INT PRIMARY KEY, Title VARCHAR (100), Author VARCHAR (100), Genre VARCHAR (50) ); CREATE TABLE Readers ( ReaderID INT PRIMARY KEY, Name VARCHAR (100), Age INT ); CREATE TABLE BorrowedBooks ( ID INT PRIMARY KEY, BookID INT, ReaderID INT, DateBorrowed DATE ); |
Analyzing Reader’s Preferences
Now we use SQL to analyze a reader’s preference based on their borrowing history. We can do this by looking at the genre of books they frequently borrow. We select the top three genres that a particular reader has borrowed the most.
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SELECT TOP 3 Genre, Count(*) AS Frequency FROM BorrowedBooks INNER JOIN Books ON BorrowedBooks.BookID = Books.BookID WHERE ReaderId = @ReaderId GROUP BY Genre ORDER BY Frequency DESC; |
Generating Recommendations
With the identified preferences, we can generate book recommendations that match these. Let’s assume the genres identified are ‘Genre1’, ‘Genre2’, and ‘Genre3’. Our SQL query will then look like:
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SELECT TOP 5 * FROM Books WHERE Genre IN ('Genre1', 'Genre2', 'Genre3') AND BookID NOT IN (SELECT BookID FROM BorrowedBooks WHERE ReaderID = @ReaderId) ORDER BY NEWID(); |
The above query selects five books randomly which the reader has not borrowed before from their top genres.
Conclusion
With a simple yet effective SQL setup, libraries can provide personalized book recommendations to their readers. This simplifies the task for librarians and provides a better reading experience for the library patrons!