一个对话的人工智能平台。
mindmeld的Python项目详细描述
Mindmeld对话人工智能平台
此存储库包含MindMeld Conversational AI Platform。
介绍mindmeld
Mindmeld对话人工智能平台是构建生产质量对话应用程序的最先进人工智能平台之一。它是一个基于python的机器学习框架，包含了实现此目的所需的所有算法和实用程序。mindmeld经过几年构建和部署数十种可实现的最先进的会话体验，经过优化，可用于构建高级会话助手，这些助手展示了对特定用例或领域的深入理解，同时提供了非常有用和多用途的会话体验。
mindmeld是目前唯一可用的会话人工智能平台，它为最先进的会话应用程序的工作流中的每一步提供工具和功能。Mindmeld的架构如下图所示。
总之，mindmeld中提供的功能包括：
高级自然语言处理，包括
- 域分类
- intent分类
- 实体识别
- 实体角色标记
- 实体解析
- 语言分析
多功能对话管理
自定义知识库创建
高级问答
培训数据收集和管理支持
大规模数据分析
mindmeld哲学
mindmeld已经被一些最大的全球组织用于数十个不同领域的应用。在这些生产部署的过程中，mindmeld已经发展成为非常适合为任何定制应用程序域构建生产质量、大词汇表语言理解能力的工具。这是通过遵循建筑哲学实现的，其指导原则如下表所示。
| Concept | Description |
|---|---|
| Power and Versatility | Unlike GUI-based tools typically too rigid to accommodate the functionality required by many applications, MindMeld provides powerful command-line utilities with the flexibility to accommodate nearly any product requirements. |
| Algorithms and Data | In contrast to machine learning toolkits which offer algorithms but little data, MindMeld provides not only state-of-the-art algorithms, but also functionality which streamlines the collection and management of large sets of custom training data. |
| NLP plus QA and DM | While conversational AI platforms available today typically provide natural language processing (NLP) support, few assist with question answering (QA) or dialogue management (DM). MindMeld provides end-to-end functionality including advanced NLP, QA, and DM, all three of which are required for production applications today. |
| Knowledge-Driven Learning | Nearly all production conversational applications rely on a comprehensive knowlege base to enhance intelligence and utility. MindMeld is the only Conversational AI platform available today which supports custom knowledge base creation. This makes MindMeld ideally suited for applications which must demonstrate deep understanding of a large product catalog, content library, or FAQ database, for example. |
| You Own Your Data | Differently from cloud-based NLP services, which require that you forfeit your data, MindMeld was designed from the start to ensure that proprietary training data and models always remain within the control and ownership of your application. |
快速启动
假设pip安装了python 3.4、python3.5、python3.6或python3.7，并且elasticsearch在后台运行：
pip install mindmeld
mindmeld blueprint home_assistant
python -m home_assistant build
python -m home_assistant converse
有关详细的安装说明，请参见Getting Started。要从预构建的示例应用程序开始，请参见MindMeld Blueprints。
引文
如果你在工作中使用mindmeld，请引用this paper：
Raghuvanshi, A., Carroll, L. and Raghunathan, K., 2018, November. Developing Production-Level Conversational Interfaces with Shallow Semantic Parsing. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations (pp. 157-162)
@inproceedings{raghuvanshi2018developing,
title={Developing Production-Level Conversational Interfaces with Shallow Semantic Parsing},
author={Raghuvanshi, Arushi and Carroll, Lucien and Raghunathan, Karthik},
booktitle={Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing:
System Demonstrations},
pages={157--162},
year={2018}
}
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