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This paper develops a principled approach to accurately identify interesting places in a city through social sensing applications. Social sensing has emerged as a new application paradigm, where a crowd of social sources (humans or devices on their behalf) collectively contribute a large amount of observations about the physical world. This paper studies an interesting place finding problem, in which...
This paper presents a scalable estimation theoretic framework to address the time-sensitive truth discovery problem with accuracy assessment in social sensing applications. Social sensing has emerged as a new application paradigm that provides us with an unprecedented opportunity to collect observations about the physical world from humans or devices on their behalf. A fundamental challenge in social...
This paper presents an unsupervised approach toaccurately discover interesting places in a city from location-basedsocial sensing applications, a new sensing applicationparadigm that collects observations of physical world fromLocation-based Social Networks (LBSN). While there are alarge amount of prior works on personalized Point of Interests(POI) recommendation systems, they used supervised learningapproaches...
Social sensing is a new application paradigm of cyber-physical-social systems (CPSS), where a group of individualsvolunteer to report their claims about the physicalenvironment using cyber devices. A fundamental problem insocial sensing application is to ascertain source reliability andthe claim correctness without knowing either of them a priori, which is referred to as truth finding. Several key...
Social sensing has emerged as a new application paradigm for smart cities where a crowd of social sources (humans or devices on their behalf) collectively contribute a large amount of observations about the physical world. This paper focuses on an interesting place finding problem in social sensing where the goal is to accurately identify the interesting places in a city where people may have strong...
This paper presents a new principled framework for exploiting time-sensitive information to improve the truth discovery accuracy in social sensing applications. This work is motivated by the emergence of social sensing as a new paradigm of collecting observations about the physical environment from humans or devices on their behalf. These observations maybe true or false, and hence are viewed as binary...
This paper develops a new principled framework for exploiting time-sensitive information to improve the truth discovery accuracy in social sensing applications. This work is motivated by the emergence of social sensing as a new paradigm of collecting observations about the physical environment from humans or devices on their behalf. These observations maybe true or false, and hence are viewed as binary...
This paper presents a spatial-temporal aware analytical framework to solve the truth finding problem in social sensing applications. Social sensing has emerged as a new big data application paradigm of collecting observations about the physical environment from social sensors (e.g., humans) or devices on their behalf. The collected observations may be true or false, and hence are viewed as binary...
This paper presents a confidence-aware maximum likelihood estimation framework to solve the truth estimation problem in social sensing applications. Social sensing has emerged as a new paradigm of data collection, where a group of individuals volunteer (or are recruited) to share certain observations or measurements about the physical world. A key challenge in social sensing applications lies in ascertaining...
This paper presents a spatial-temporal aware analytical framework to solve the truth finding problem in social sensing applications. Social sensing has emerged as a new big data application paradigm of collecting observations about the physical environment from social sensors (e.g., humans) or devices on their behalf. The collected observations may be true or false, and hence are viewed as binary...
This paper presents a demonstration of our SECON 2015 paper using Twitter based case studies for social sensing applications. Social sensing has emerged as a new paradigm of data collection, where a group of individuals volunteer (or are recruited) to share certain observations or measurements about the physical world. A key challenge in social sensing applications lies in ascertaining the correctness...
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