Developing a Domain-based Ontology using Permanent Banking Instructions

近年来，多个领域的大数据在世界范围内显著崛起。此外，随着大数据和机器学习算法的日益普及，我们正处于基于领域的信息爆炸时代。因此，为特定领域的大数据开发足够的自然语言处理和机器学习工具是非常重要和必要的。为更好的信息分析和可视化，对这些数据进行建模、分类和重用开发的资源也很重要。通过构建计算工具和语言资源，如特定领域本体，加拿大国家银行将能够将这些资源纳入现有的大数据分析管道，在对话代理和信息检索的设计中组合和重用，从而为他们的社区提供更完整和智能的产品。当前的研究项目旨在使用永久银行指令创建基于领域的本体。从特定领域的数据开始，这个合作项目的目标是使用适当的工具和技术对基于大型领域的语料库进行预处理，这些工具和技术将考虑金融领域和语言（在这种情况下是法语），从特定领域的语料库中提取特定领域的概念和这些概念之间的语义关系。特定领域本体将成为加拿大国家银行人工智能和大数据分析管道中的宝贵资源。

In recent years, big data of several domains has risen significantly to prominence in the world. Moreover, withthe increasing popularity of big data and machine learning algorithms, we are in the era of domain-basedinformation explosion. Therefore, it is important and necessary to develop adequate NLP and machine learningtools for the domain-specific big data. It is also important to model, classify this data and reuse the developedresources, for better information analytics and visualization. By building computational tools and linguisticresources such as a domain-specific ontology, the National Bank of Canada will be able to involve thisresource in the existing Big Data Analytics pipeline, combine and reuse it in the design of a conversationalagent and information retrieval, and thus provide more complete and intelligent product for their community.The current research project aims at creating a domain-based ontology using permanent banking instructions.Starting from domain-specific data, this collaborative project targets the pre-processing of a largedomain-based corpus using adequate tools and techniques that will consider the financial domain and thelanguage (French, in this case), the extraction of domain-specific concepts and semantics relationshipsbetween these concepts from the domain-specific corpus.The domain-specific ontology will be a valuable resource in the AI and big data analytics pipeline of theNational Bank of Canada.