我在客户和顾问之间进行了聊天互动[对话]，并且想知道顾问互动是否包含下面列表中的特定句子或类似句子：
[我正在顾问互动中寻找的例句
["I would be more than happy to help you with this",
"I would be happy to look over the account to see how I can help get this sorted out for you",
"I’d be more than happy to look into this for you!",
"Oh, I see, let me assist you with this concern.",
"I am more than happy to do everything I can to resolve this matter for you.",
"I would be happy to look over the account to see how I can help get this sorted out for you.",
"I am happy to have a look."]
I have a dataset which contains the list of interaction_id and Utterances(Sample below)
```Example Chat interaction between Advisor and CLient :
Client : Hello I would like to place an order for replacement battery
Agent: Hi Welcome to Battery service department. I would be happy to help you with your battery replacement Order.
如何获取/提取具有相似意图或含义的句子。我是NLP的新手，我认为我手头有一个句子分类/提取问题，想知道有什么方法可以实现我所需要的]
基本上我正在尝试实现以下目标：
ID Utt Help_Stmt_Present
IRJST Hi Welcome to Battery service department.
I would be happy to help you with your battery
replacement Order. Yes
可以采用多种方法在多个步骤中执行此操作：1。计算句子向量
a。使用预训练的单词嵌入（手套，word2vec，fasttext等）并为每个单词计算单词嵌入，然后将其平均到句子的单词中，以计算句子的嵌入。b。使用Universal Sentence Encoder获取句子嵌入。
2。计算相似度匹配
a。使用欧几里得或余弦或其他最适合您的问题的距离度量，计算目标与所有其他N个句子之间的距离。b。使用您拥有的N个句子向量训练KNN模型，并对目标句子应用K-NN预测以获得K个最相似的句子。
为了获得更好的结果，您可以使用基于深度学习的技术和SOTA体系结构，例如变压器及其之上构建的体系结构。您可以签出this repository，这可以使用变压器解决您的任务。同样，要使用不同的体系结构和其他NLP任务，您可以签出Hugging Face Repository