Reference number : GC-2017-Q4-01400, amendment number : , agreement type : G, recipient legal name : Papagelis, Manos (York University)|Papagelis, Manos (Université York), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : With the growing use of mobile devices, users increasingly expect to find more local and time-sensitive_x000D_
information, such as the new popular restaurant or the hidden café around the corner. In this project, we aim to_x000D_
leverage big data and machine learning to address the problem of providing accurate and timely answers to user_x000D_
questions from local experts. In particular, the industrial partner has developed a mobile app that facilitates_x000D_
location-based question-answering services. These services allow users to use their mobile phone to ask_x000D_
questions and find local information by interacting with local experts. A key to the success of these services is_x000D_
the quality and timeliness of the responses provided by directing user questions to the right expert in a_x000D_
database. The main objective of this collaborative project is to address this problem by designing and_x000D_
developing algorithms for finding and ranking experts in a database._x000D_
The anticipated outcome of the research is twofold: (i) a framework for automatically enhancing a user's_x000D_
expertise profile, and (ii) novel algorithms, strategies and tools that can find and rank local experts that can_x000D_
provide useful and timely answers. The scientific approach of our research is characterized by processing,_x000D_
modeling, analysis of large data sets and involves the use of advanced techniques for data analysis, such as text_x000D_
analytics, machine learning, predictive analytics, and natural language processing._x000D_
The proposed research collaboration aligns with Canada's Innovation Agenda. Conducting research in the_x000D_
intersection of big data analytics and machine learning has the potential to attract the brightest students from_x000D_
around the world, while keeping domestic talent here. Meanwhile, it will contribute to the training of high_x000D_
quality personnel, with first-rate analytical and problem-solving skills that have the capacity to stimulate_x000D_
knowledge-based companies and boost productivity and innovation taking place across Canada., program purpose french : With the growing use of mobile devices, users increasingly expect to find more local and time-sensitive_x000D_
information, such as the new popular restaurant or the hidden café around the corner. In this project, we aim to_x000D_
leverage big data and machine learning to address the problem of providing accurate and timely answers to user_x000D_
questions from local experts. In particular, the industrial partner has developed a mobile app that facilitates_x000D_
location-based question-answering services. These services allow users to use their mobile phone to ask_x000D_
questions and find local information by interacting with local experts. A key to the success of these services is_x000D_
the quality and timeliness of the responses provided by directing user questions to the right expert in a_x000D_
database. The main objective of this collaborative project is to address this problem by designing and_x000D_
developing algorithms for finding and ranking experts in a database._x000D_
The anticipated outcome of the research is twofold: (i) a framework for automatically enhancing a user's_x000D_
expertise profile, and (ii) novel algorithms, strategies and tools that can find and rank local experts that can_x000D_
provide useful and timely answers. The scientific approach of our research is characterized by processing,_x000D_
modeling, analysis of large data sets and involves the use of advanced techniques for data analysis, such as text_x000D_
analytics, machine learning, predictive analytics, and natural language processing._x000D_
The proposed research collaboration aligns with Canada's Innovation Agenda. Conducting research in the_x000D_
intersection of big data analytics and machine learning has the potential to attract the brightest students from_x000D_
around the world, while keeping domestic talent here. Meanwhile, it will contribute to the training of high_x000D_
quality personnel, with first-rate analytical and problem-solving skills that have the capacity to stimulate_x000D_
knowledge-based companies and boost productivity and innovation taking place across Canada., agreement title english : Ranking Experts in Location-aware Question-Answering Services, agreement title french : Ranking Experts in Location-aware Question-Answering Services, agreement number : EGP, agreement value : 25000.0, agreement start date : 2018-03-07, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada