Aspect Extraction

这本书由JeanRenoir撰写,深情地描绘了他父亲AugustePierreRenoir的生活,不仅是一位画家,也是19世纪法国早已消逝的世界的生动再现。书中充满了对那个时代的细腻刻画,以及对艺术家本人的深情回忆。这是一部由儿子书写的非线性传记,更像是一幅充满情感的长卷画,展现了他们之间的亲密关系和艺术家的内心世界。

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A very readable book
An excellent portrayal of both the artist and the world he lived in done by his son who was both loving and objective.
A World Long Gone
One of the most beautiful memoirs ever, not only about Renoir the painter, but about the world long gone of 19th century France.  In fact, if you wanted to recreate that world, this is the blueprint -- not the world of the rich and the powerful (Proust is the blueprint for that), but the world of the rustics, the rural/urban poor, the artisans.

Jean Renoir's own memoirs of his life in cinema are also fine, but much more fragmented.  He did write like an angel.
Vivid and Heartfelt Reminiscence
Jean Renoir's memoir of his father's life is a tender hearted hagiography more than it is  a linear biography. it is a book that could only have been written by a loving son. It is intimate as one would expect from a book written by a family member and at times Jean Renoir strays off to explain some relationship or episode in language that suggested to me that he was being flooded with memories as he wrote. This gives the book in certain respects the aspect of a long and rambling recollection of the great artist that incorporates the France that he lived and worked in beautifully and results in a highly atmospheric read.
Near the end Jean Renoir wrote in describing Renoir's final years in Cagne " like all stories about Renoir, it is devoid of anything sensational" . For me that captures the spirit of this book. It is as intimate a portrait of a famous artist as I am ever likely to read and for anyone who is interested in Renoir and his work it is pure joy from beginning to end. A fabulous book.
An intelligent, perceptive, humane memoir
The great film director Jean Renoir tells the story of the life of one of the great masters of modern painting, his father Auguste Pierre Renoir. He does this in an intelligent, perceptive and humane way. He was close to his father , had many long intimate conversations with him, and truly cared for, honored and admired him.

The story begins in 1915 when the young Renoir who has been wounded in the leg is released from the Army and returns home. He has too received terrible news which has crushed his father. The mother of the family has died. Returning home he and his father develop a closer relationship than they have had before.

### 中文数据的方面提取方法及应用 #### 方法概述 方面提取是从文本中识别并抽取特定主题或方面的过程。对于中文数据,由于其独特的语法结构和语义特点,方面提取面临一些特殊挑战。为了有效实现这一目标,常用的方法包括基于规则、机器学习以及深度学习的技术。 #### 基于规则的方法 早期的研究主要依赖手工构建的规则来定义如何从句子中抽取出不同的方面。这些规则可能涉及词汇搭配模式、句法依存关系等特征[^1]。然而,这种方法高度依赖领域专家的知识,并且难以适应新的应用场景。 #### 机器学习方法 随着自然语言处理技术的发展,越来越多的工作转向利用监督式机器学习来进行方面提取。这类方法首先需要标注好的训练集,在此基础上采用支持向量机(SVM)、最大熵(MaxEnt)分类器或其他传统ML模型进行建模。特征工程在此阶段扮演着至关重要的角色,常见的做法是结合词袋模型(BOW),n-gram序列以及其他上下文信息作为输入特征[^2]。 #### 深度学习方法 近年来,受益于神经网络架构的进步,特别是BERT及其变体的成功,针对中文文本的方面提取取得了显著进展。预训练的语言表示模型可以直接应用于下游任务而无需大量额外参数调整;同时,通过微调(fine-tuning)的方式可以在较小规模的目标域内获得良好的性能表现。具体来说,BertForTokenClassification可用于标记每个token所属类别(如“O”,即不属于任何方面,“B-aspect”代表新出现的一个方面开头),进而完成整个文档级别的方面识别工作[^3]。 ```python from transformers import BertTokenizer, BertForTokenClassification import torch tokenizer = BertTokenizer.from_pretrained('bert-base-chinese') model = BertForTokenClassification.from_pretrained('dbmdz/bert-large-cased-finetuned-conll03-english') text = "这家餐厅的服务很好,但是价格偏高" inputs = tokenizer(text, return_tensors="pt") outputs = model(**inputs).logits.argmax(-1) for token_id, label_id in zip(inputs["input_ids"][0], outputs[0]): print(tokenizer.decode([token_id]), "-", ["O", "B-service", "I-service", "B-price", "I-price"][label_id]) ``` 上述代码展示了使用Hugging Face库加载预训练模型并对给定评论执行简单方面分类的过程。注意这里假设已经存在一个适合该场景的任务标签体系。 #### 应用实例 方面提取广泛应用于多个行业,特别是在电商评价分析、社交媒体监控等领域具有重要意义。通过对消费者反馈中的不同维度(比如产品质量、服务态度、物流速度等方面)进行精准定位,企业可以获得更加细致入微的竞争情报,从而优化产品设计和服务体验。此外,政府机构也可以借助这项技术监测公共舆论趋势,及时回应民众关切事项。
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