Cornell_Movie-Dialogs 代码

作为AI助理，我不能为您提供代码，但是我可以为您提供一些有关Cornell Movie-Dialogs数据集的信息和示例代码。

Cornell Movie-Dialogs数据集是一个包含电影对话的数据集，由Cornell大学电影研究计划创建。该数据集包含超过220,579行对话，来自617部电影的10,292个角色。每个角色都有自己的ID，每行对话都有一个唯一的ID。数据集还包括电影元数据，如标题，年份和IMDB评分。

对话数据集可以用于许多NLP任务，如情感分析，对话生成和对话系统。

以下是一个示例代码来加载和处理Cornell Movie-Dialogs数据集：

import os

# Set the path to the dataset folder
data_folder = os.path.join(os.getcwd(), 'cornell movie-dialogs corpus')

# Define the path to the files we will be using
movie_lines_file = os.path.join(data_folder, 'movie_lines.txt')
movie_conversations_file = os.path.join(data_folder, 'movie_conversations.txt')

# Load the lines from the file
with open(movie_lines_file, 'r', encoding='iso-8859-1') as f:
    lines = f.readlines()

# Create a dictionary to store the lines
id_to_line = {}
for line in lines:
    parts = line.split(' +++$+++ ')
    if len(parts) == 5:
        line_id = parts[0]
        text = parts[4]
        id_to_line[line_id] = text

# Load the conversations from the file
with open(movie_conversations_file, 'r', encoding='iso-8859-1') as f:
    conversations = f.readlines()

# Create a list to store the conversations
conversation_ids = []
for conversation in conversations:
    parts = conversation.split(' +++$+++ ')
    if len(parts) == 4:
        conversation_ids.append(parts[3][1:-2].replace("'", "").split(", "))

# Create a list to store the conversations as text
conversations_text = []
for conversation in conversation_ids:
    conversation_text = []
    for i in range(len(conversation) - 1):
        conversation_text.append(id_to_line[conversation[i]].strip())
    conversations_text.append(conversation_text)

print(conversations_text[:10])

此代码将打印前10个对话。