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An automated multi-web platform voting framework to predict misleading information proliferated during COVID-19 outbreak...

Published in Data & knowledge engineering

The spreading of misleading information on social web platforms has fuelled massive panic and confusion among the public regarding the Corona disease, the detection of which is of paramount importance. Previous studies mainly relied on a specific web platform to collect crucial evidence to detect fake content. The analysis identifies that retrievin...

Deep learning in the COVID-19 epidemic: A deep model for urban traffic revitalization index.

Published in Data & knowledge engineering

The research of traffic revitalization index can provide support for the formulation and adjustment of policies related to urban management, epidemic prevention and resumption of work and production. This paper proposes a deep model for the prediction of urban Traffic Revitalization Index (DeepTRI). The DeepTRI builds model for the data of COVID-19...

Reducing the bottleneck of graph-based data mining by improving the efficiency of labeled graph isomorphism testing

Published in Data & Knowledge Engineering

Geospatial data streams: Formal framework and implementation

Published in Data & Knowledge Engineering

Detecting summarizability in OLAP

Published in Data & Knowledge Engineering

Editorial Board

Published in Data & Knowledge Engineering

A semi supervised learning model for mapping sentences to logical forms with ambiguous supervision

Published in Data & Knowledge Engineering

Automatically Generating Data Linkages Using Class-Based Discriminative Properties

Published in Data & Knowledge Engineering

Mining frequent itemsets in data streams within a time horizon

Published in Data & Knowledge Engineering

Extending ER models to capture database transformations to build data sets for data mining

Published in Data & Knowledge Engineering