diff --git a/cxy.py b/cxy.py
index 12fd740..e620e0e 100644
--- a/cxy.py
+++ b/cxy.py
@@ -1,31 +1,63 @@
-#第一题
-str1 = "Hello"
-str2 = 'Hello'
-
-print("双引号表示：", str1)
-print("单引号表示：", str2)
-print("两种表示方式是否相同：", str1 == str2)
-
-print("\n--- Hello 每个字符的 ASCII 码 ---")
-for char in "Hello":
-    print(f"字符 {char} 的ASCII码：{ord(char)}")
-
-print("\n--- chr() 函数验证 ---")
-result = chr(65)
-print(f"数字65通过chr()转换后是：{result}")
-print(f"65对应字符是否为大写A：{result == 'A'}")
-
-#第二题
+# -------------------- 题目3 --------------------
 import math
 
 A = [3, 4]
 B = [1, 2]
 
-add_result = [A[0] + B[0], A[1] + B[1]]
-print("A + B =", add_result)
+print("题目3")
+print("A + B =", [A[0]+B[0], A[1]+B[1]])
+print("2 × A =", [2*A[0], 2*A[1]])
+print("A 的长度 =", math.sqrt(A[0]**2 + A[1]**2))
+print()
 
-mul_result = [2 * A[0], 2 * A[1]]
-print("2 × A =", mul_result)
+# -------------------- 题目4 --------------------
+A = [1,2,3]
+B = [4,5,6]
 
-norm_A = math.sqrt(A[0]**2 + A[1]**2)
-print("A 的模 =", norm_A)
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+dot = sum(a*b for a,b in zip(A,B))
+normA = math.sqrt(sum(x**2 for x in A))
+normB = math.sqrt(sum(x**2 for x in B))
+cos = dot / (normA * normB)
+
+print("题目4")
+print("点积 =", dot)
+print("余弦相似度 =", round(cos, 4))
+
+A2 = [1,0]
+B2 = [0,1]
+dot2 = A2[0]*B2[0] + A2[1]*B2[1]
+normA2 = math.sqrt(A2[0]**2 + A2[1]**2)
+normB2 = math.sqrt(B2[0]**2 + B2[1]**2)
+cos2 = dot2 / (normA2 * normB2)
+print("A=[1,0], B=[0,1] 余弦相似度 =", cos2)
+print()
+
+# -------------------- 题目5 BoW --------------------
+from sklearn.feature_extraction.text import CountVectorizer
+
+docs = [
+    "Python 是 编程 语言",
+    "Java 是 编程 语言",
+    "Python Python Python"
+]
+
+bow = CountVectorizer()
+matrix = bow.fit_transform(docs)
+
+print("题目5")
+print("词表 =", list(bow.get_feature_names_out()))
+print("文档向量：")
+print(matrix.toarray())
+print()
+
+# -------------------- 题目7 TF-IDF --------------------
+from sklearn.feature_extraction.text import TfidfVectorizer
+
+docs = ["Python 编程", "Java 编程", "Python Python"]
+tfidf = TfidfVectorizer()
+matrix = tfidf.fit_transform(docs)
+
+print("题目7")
+print("词表:", tfidf.get_feature_names_out())
+print("TF-IDF矩阵:")
+print(matrix.toarray().round(4))
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