Ranking Experts in Location-aware Question-Answering Services

随着移动设备的使用越来越多，用户越来越希望找到更多当地的、对时间敏感的信息，比如新的受欢迎的餐厅或拐角处隐藏的咖啡馆。在这个项目中，我们的目标是利用大数据和机器学习来解决为当地专家的用户问题提供准确和及时的答案的问题。特别是，这家工业合作伙伴开发了一款移动应用程序，为基于位置的问答服务提供便利。这些服务允许用户使用他们的手机提问，并通过与当地专家互动来查找当地信息。这些服务成功的一个关键是通过将用户问题导向数据库中的适当专家而提供的答复的质量和及时性。这个合作项目的主要目标是通过设计和开发在数据库中寻找和排名专家的算法来解决这个问题。研究的预期结果有两个：(I)自动增强用户专业知识档案的框架，以及(Ii)可以找到并排名当地专家的新算法、策略和工具，这些专家可以提供有用和及时的答案。我们研究的科学方法的特点是处理、建模、分析大数据集，并使用先进的数据分析技术，如文本分析、机器学习、预测分析和自然语言处理。建议的研究合作符合加拿大的创新议程。在大数据分析和机器学习的交叉领域进行研究，有可能吸引世界各地最聪明的学生，同时留住国内人才。同时，它将有助于培训高素质的人员，拥有一流的分析和解决问题的技能，有能力刺激以知识为基础的公司，并提高加拿大各地的生产率和创新。

With the growing use of mobile devices, users increasingly expect to find more local and time-sensitiveinformation, such as the new popular restaurant or the hidden café around the corner. In this project, we aim toleverage big data and machine learning to address the problem of providing accurate and timely answers to userquestions from local experts. In particular, the industrial partner has developed a mobile app that facilitateslocation-based question-answering services. These services allow users to use their mobile phone to askquestions and find local information by interacting with local experts. A key to the success of these services isthe quality and timeliness of the responses provided by directing user questions to the right expert in adatabase. The main objective of this collaborative project is to address this problem by designing anddeveloping algorithms for finding and ranking experts in a database.The anticipated outcome of the research is twofold: (i) a framework for automatically enhancing a user'sexpertise profile, and (ii) novel algorithms, strategies and tools that can find and rank local experts that canprovide useful and timely answers. The scientific approach of our research is characterized by processing,modeling, analysis of large data sets and involves the use of advanced techniques for data analysis, such as textanalytics, machine learning, predictive analytics, and natural language processing.The proposed research collaboration aligns with Canada's Innovation Agenda. Conducting research in theintersection of big data analytics and machine learning has the potential to attract the brightest students fromaround the world, while keeping domestic talent here. Meanwhile, it will contribute to the training of highquality personnel, with first-rate analytical and problem-solving skills that have the capacity to stimulateknowledge-based companies and boost productivity and innovation taking place across Canada.