An Enterprise Answering System for Collaborative Question Answering Platforms

协作问答平台的企业问答系统

• 批准号: 537219-2018
• 负责人: Zihayatkermani, Morteza
• 金额: $ 5.25万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=720255
• 关键词: Enterprise; Answering; System; Collaborative; Question

Community Question-Answering (CQA) platforms, such as Stackoverflow, Quora, and Yahoo! Answers, have become popular sources of information over the past several years. As the number of questions increases, it becomes harder for users to track questions that are most relevant to them. As a result the quality of attention that different questions receive on the a platform becomes highly dependent on many contextual and social processes. Our industrial partner, IBM aims to become more responsive to communities of inquiry and addresses concerns and questions raised by customers regarding different IBM products effectively. IBM strives to automatically identify these threads of questions and addresses them effectively. While such questions might have an answer in internal enterprise resources or there is an IBM expert who is able to address the question effectively, such questions will be remained unanswered, thus increasing customer dissatisfaction and disengagement. Therefore, appropriate techniques are required that would look into questions posted by customers in the public domain and search internal resources (e.g., knowledge bases, internal expert knowledge) in order to efficiently address the customer's information needs and work towards their satisfaction.Our work will concentrate on formulating a multi-faceted framework that will collectively consider semantics of contents, analysis on available resources and effective allocation, and monitoring and predicting the quality of the provided answers in order to build a system that can extract the best answer effectively and efficiently. We believe that developing a coherent and effective QA system increases satisfaction for IBM's customers, and increases IBM's competitive advantage. As a result, it will be directly beneficial to Canada as more revenue for IBM Canada means more investment from IBM in Canada and hiring more Canadian talent.

社区搜索引擎（CQA）平台，如Stackoverflow、Quora和Yahoo！在过去的几年里，答案已经成为流行的信息来源。随着问题数量的增加，用户越来越难以跟踪与他们最相关的问题。因此，不同问题在平台上获得的关注质量高度依赖于许多上下文和社会过程。我们的工业合作伙伴IBM旨在更好地响应社区的调查，并有效地解决客户对不同IBM产品提出的问题。IBM致力于自动识别这些问题线索并有效地解决它们。虽然这些问题可能在内部企业资源中有答案，或者有一个IBM专家能够有效地解决这个问题，但这些问题将仍然没有答案，从而增加客户的不满和脱离。因此，需要适当的技术来研究客户在公共领域中发布的问题并搜索内部资源（例如，知识库、内部专家知识），以有效地满足客户的信息需求，并致力满足他们的需求。我们的工作将集中于制定一个多方面的框架，综合考虑内容的语义、可用资源的分析和有效分配，以及监控和预测所提供的答案的质量，以便构建能够有效且高效地提取最佳答案的系统。我们相信，开发一个连贯而有效的QA系统可以提高IBM客户的满意度，并增强IBM的竞争优势。因此，这将直接有利于加拿大，因为IBM加拿大公司的更多收入意味着IBM在加拿大的更多投资和雇用更多的加拿大人才。