Part1.BasicRecAlgorithms/userItemCF_15label.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7057c784-3286-431c-baf2-b926bfff5cf5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import collections\n",
    "import nbimporter\n",
    "import basicSim\n",
    "import userCF_01label\n",
    "from tqdm import tqdm\n",
    "import csv\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "234e9f7e-a980-4ca2-a689-86e860b1bf30",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_triples(file_path):\n",
    "    \"\"\"\n",
    "    从指定文件中读取用户-物品-评分的三元组。\n",
    "    \n",
    "    参数：\n",
    "        file_path (str): 指定文件路径，例如 'rating_index.tsv'。\n",
    "        \n",
    "    返回：\n",
    "        list of tuples: 返回一个包含 (user, item, rating) 三元组的列表。\n",
    "    \"\"\"\n",
    "    triples = []  # 初始化一个空列表用于存储三元组\n",
    "    with open(file_path, 'r', newline='') as file:\n",
    "        reader = csv.reader(file, delimiter='\\t')  # 使用制表符分隔\n",
    "        for row in reader:\n",
    "            user, item, rating = map(int, row)  # 转换为整数类型\n",
    "            triples.append((user, item, rating))  # 将三元组添加到列表中\n",
    "    return triples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "74a03c35-2790-4106-bc73-cf40febf0e01",
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       " ...]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "triples = read_triples(\"rating_index.tsv\")\n",
    "triples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2738adcc-1966-4e15-930e-e7f1a4bf920a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def getDict(triples):\n",
    "    \"\"\"\n",
    "    将三元组数据转换为用户-物品和物品-用户字典。\n",
    "\n",
    "    参数：\n",
    "        triples (iterable): 一个三元组列表，每个三元组的形式为 (用户 ID, 物品 ID, 评分)。\n",
    "                             例如：[(u1, i1, r1), (u2, i2, r2), ...]\n",
    "\n",
    "    返回：\n",
    "        tuple: 包含两个字典的元组：\n",
    "            - user_items (defaultdict(dict)): 用户与物品及其评分的映射，结构为 {用户 ID: {物品 ID: 评分, ...}, ...}。\n",
    "            - item_users (defaultdict(dict)): 物品与用户及其评分的映射，结构为 {物品 ID: {用户 ID: 评分, ...}, ...}。\n",
    "\n",
    "    功能：\n",
    "        该函数将输入的三元组数据转换为两个字典，便于快速访问用户对物品的评分以及物品对用户的评分。\n",
    "    \"\"\"\n",
    "    \n",
    "    user_items = collections.defaultdict(dict)\n",
    "    item_users = collections.defaultdict(dict)\n",
    "    for u,i,r in triples:\n",
    "        user_items[u][i] = r\n",
    "        item_users[i][u] = r\n",
    "    return user_items, item_users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b77ec60d-452e-4bf9-ad92-e1e84f504c44",
   "metadata": {},
   "outputs": [],
   "source": [
    "def getCosSimForDict(d1,d2):\n",
    "    s1 = set(d1.keys())\n",
    "    s2 = set(d2.keys())\n",
    "    inner = s1 & s2\n",
    "    if len(inner) == 0:\n",
    "        return 0\n",
    "    a1,a2 = [],[]\n",
    "    all_keys = set(d1.keys()).union(set(d2.keys()))\n",
    "    for key in all_keys:\n",
    "        a1.append(d1.get(key, 0))  # 如果key不在d1中，则使用0\n",
    "        a2.append(d2.get(key, 0))  # 如果key不在d2中，则使用0\n",
    "    return basicSim.cos4vector(np.array(a1),np.array(a2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "27a989bc-c747-4242-85c6-66d5219be7b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cosine Similarity: 0.8315218406202999\n"
     ]
    }
   ],
   "source": [
    "d1 = {1: 1, 2: 2, 3: 3}\n",
    "d2 = {2: 5, 3: 4, 4: 3}\n",
    "cos_sim = getCosSimForDict(d1, d2)\n",
    "print(\"Cosine Similarity:\", cos_sim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "03956b85-729e-45bf-8b05-3238ee7d2b60",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
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