Ranking Experts in Location-aware Question-Answering Services

位置感知问答服务专家排名

• 批准号: 521777-2017
• 负责人: Papagelis, Manos
• 金额: $ 1.82万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640116
• 关键词: Ranking; Experts; Location; aware; Question

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.

随着移动的设备的使用越来越多，用户越来越希望找到更多的本地和时间敏感的信息，如新的流行餐厅或隐藏的咖啡馆在拐角处。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，工业合作伙伴开发了一个移动的应用程序，促进基于位置的问答服务。这些服务允许用户使用他们的移动的电话来提问，并通过与当地专家的互动来查找当地信息。这些服务成功的关键是通过将用户问题引导到数据库中合适的专家来提供响应的质量和及时性。该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。该研究的预期成果有两个方面：（i）自动增强用户专业知识概况的框架，以及（ii）可以找到和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，分析大型数据集，并涉及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。拟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。与此同时，它将有助于培训高素质的人员，他们具有一流的分析和解决问题的技能，有能力刺激知识型公司，提高加拿大各地的生产力和创新能力。