Linking External Sources to Legal Contracts using Semantic Similarity

该项目解决了在公司环境中自动处理已签署合同的问题。这个 Industries Collaborator是一家名为PACTA的公司，它帮助公司跟踪他们签署的所有合同 团队、部门和组织。该项目的重点是识别外部文件的任务 可能影响合同的来源，如相关法律文件。我们的方法是基于细分的 文档和合同，以及使用网络n-gram语料库的语义相似度。这个词以n元语法为基础 方法将是完全无监督的，并且它可以扩展到英语以外的语言。这种方法是 基于Dalhousie研究小组现有的专业知识。最终目标是加速和改进 搜索能够找到与合同密切相关的最合适的候选文档，从而减少 人类在这一过程中的努力。该项目将对PACTA的功能和功能产生明显和可衡量的影响 价值主张。与达尔豪西大学的合作将对双方都有利，因为它将 允许PACTA以更快的速度向用户提供新的创新功能和Dalhousie大学 以获取一系列商业协议，用于未来的研究和开发。结果就是 本提案中包含的研究将使公司能够扩大向客户提供的服务，以及 从而增强其竞争地位，增加服务的出口潜力。

This project addresses the problem of automated processing of signed contracts in corporate environment. The industrial collaborator, the PACTA company, helps companies keep track of their signed contracts across teams, departments, and organizations. The project is focused on the task of identifying external document sources that may affect the contracts, such as relevant legal documents. Our approach is based on segmentation of documents and contracts, and semantic similarity using web n-gram corpora. This word n-gram based approach would be fully unsupervised, and it is extensible to language other than English. This approach is based on the existing expertise of the Dalhousie research team. The ultimate goal is to accelerate and improve search ability to find most appropriate candidate documents that are strongly related to the contract, reducing human effort in the process. The project will have a clear and measurable impact on PACTA's functionality and value proposition. The collaboration with Dalhousie University will be of benefit to both parties in that it will allow PACTA to deliver a new and innovative functionality to users at a faster pace and Dalhousie University to get access to a corpus of commercial agreements for future research and development. The result of the research contained in this proposal will enable the company to expand the services offering to its clients, and thereby enhance its competitive position and increase export potential of the services.