update

app.py

@@ -33,7 +33,7 @@ def recommend_books(user_id):
     book_df = pd.read_csv(info_path)
     book_df = book_df[book_df["Num-Rating"] > lb]
     book_df['predict'] = book_df["ISBN"].map(predict_dict)
-    df = book_df.nlargest(num, "predict").reset_index(drop=True)
+    df = book_df.nlargest(num, ["predict", "Mean-Rating"]).reset_index(drop=True)
     df["context"] = df.apply(
         lambda book: f"{book['Book-Title']} ({book['Year-Of-Publication']}) - by {book['Book-Author']}", axis=1
     )

preprocessing.py

@@ -68,9 +68,11 @@ def main(
     }
 
     book_df = pd.read_csv(book_path, delimiter=';', encoding='ISO-8859-1', on_bad_lines='skip')
+    book_df = book_df[book_df["ISBN"].isin(book_id_map.keys())]
     summary_rating = data.groupby("ISBN").agg(function, axis=0)
     summary_rating = summary_rating.rename(columns={"Book-Rating": "Mean-Rating", "User-ID": "Num-Rating"})
     df = book_df.merge(summary_rating, how="left", left_on="ISBN", right_on="ISBN")
+    df = df.dropna()
     df.drop(columns=["Image-URL-S", "Image-URL-M", "Image-URL-L"], inplace=True)
     df.to_csv(f"{out_dir_path}/summary_book.csv", index=False)
 

recommend.py

@@ -44,10 +44,7 @@ def main(
     book_df = pd.read_csv(info_path)
     book_df = book_df[book_df["Num-Rating"] > lb]
     book_df['predict'] = book_df["ISBN"].map(predict_dict)
-    recommendations = book_df.nlargest(num, "predict").reset_index(drop=True)
-    recommendations["context"] = recommendations.apply(
-        lambda book: f"{book['Book-Title']} ({book['Year-Of-Publication']}) - by {book['Book-Author']}", axis=1
-    )
+    recommendations = book_df.nlargest(num, ["predict", "Mean-Rating"]).reset_index(drop=True)
     print(recommendations)
 
 

weight/W.npy

@@ -1,3 +1,3 @@
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-oid sha256:8df3995b7b6243c4b68b3cecabb10414d982c1cf1baf4533e6c8b8fadd3dc751
+oid sha256:0e1757d82be4290dd18219aed88c0bf5df6953b2f3af4cf338e29b0c93a70f64
 size 13248

weight/X.npy

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d9f0e114c605d0b60edbf581ae35380ec3f1a1271f280d3f17c415a52828358f
+oid sha256:8ebb19a4f9774534e5775ea46fe36703eb3d48d8e277dff23e7a86e6d67bcf2c
 size 79008

weight/b.npy

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d69013d3a83302293d5e37e4fbbb2dd026297f6499cd71d9501fc91adc0d817f
+oid sha256:ab2d9d72e616728b7060219a68f925d533deade86b437b115c4eed1b44d36e71
 size 1440

weight/predicted.npy

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8d02e08da558c5ad31c1eb64d15a6227b570ef73c4d0597d5ab49a5aa7f0310f
+oid sha256:5d660b11ee4be0eee7f7a66d1b5bfebef5bdc50d253454c30a5c83334e7c3784
 size 1293760