DLFTI: A deep learning based fast truth inference mechanism for distributed spatiotemporal data in mobile crowd sensing
Abstract The paradigm of Mobile Crowd Sensing (MCS) allows for numerous applications
with distributed spatiotemporal data, where great attention is drawn to the fundamental …
with distributed spatiotemporal data, where great attention is drawn to the fundamental …
A Survey on Truth Discovery: Concepts, Methods, Applications, and Opportunities
In the era of data information explosion, there are different observations on an object (eg, the
height of the Himalayas) from different sources on the web, social sensing, crowd sensing …
height of the Himalayas) from different sources on the web, social sensing, crowd sensing …
A survey of big data dimensions vs social networks analysis
The pervasive diffusion of Social Networks (SN) produced an unprecedented amount of
heterogeneous data. Thus, traditional approaches quickly became unpractical for real life …
heterogeneous data. Thus, traditional approaches quickly became unpractical for real life …
ATWR-SMR: an area-constrained truthful worker recruitment based sensing map recovery scheme for sparse MCS in extreme-environment internet-of-things
Sparse mobile crowdsensing (SMCS) is a prospective solution for large-scale data sensing
through mobile devices of Internet of Things (IoT) systems where IoT systems cannot obtain …
through mobile devices of Internet of Things (IoT) systems where IoT systems cannot obtain …
Social sensing in IoT applications: A review
A Pandharipande - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
The proliferation of the Internet and mobile devices has led to users increasingly
communicating with each other and expressing themselves on a variety of digital channels …
communicating with each other and expressing themselves on a variety of digital channels …
RPTD: Reliability-enhanced privacy-preserving truth discovery for mobile crowdsensing
Y Liu, F Liu, HT Wu, J Yang, K Zheng, L Xu… - Journal of Network and …, 2022 - Elsevier
Mobile CrowdSensing (MCS) provides effective data collection through smart devices
carried by users. However, the data sensed from various devices is privacy-sensitive and not …
carried by users. However, the data sensed from various devices is privacy-sensitive and not …
A joint maximum likelihood estimation framework for truth discovery: A unified perspective
Truth discovery algorithms have been widely applied to identify the true claims from the
conflicting information provided by multiple sources. In general, they conduct an iterative …
conflicting information provided by multiple sources. In general, they conduct an iterative …
Computational modeling of hierarchically polarized groups by structured matrix factorization
The paper extends earlier work on modeling hierarchically polarized groups on social
media. An algorithm is described that 1) detects points of agreement and disagreement …
media. An algorithm is described that 1) detects points of agreement and disagreement …
RMDF-CV: a Reliable Multi-source Data Fusion Scheme with Cross Validation for Quality Service Construction in Mobile Crowd Sensing
Mobile Crowd Sensing is a prevalent and efficient paradigm for multi-source data collection,
where Multi-source Data Fusion (MDF) plays a crucial role in constructing quality data …
where Multi-source Data Fusion (MDF) plays a crucial role in constructing quality data …
A Multi-classification Division-aggregation Framework for Fake News Detection
Nowadays, as human activities are shifting to social media, fake news detection has been a
crucial problem. Existing methods ignore the classification difference in online news and …
crucial problem. Existing methods ignore the classification difference in online news and …