Complex event recognition in the big data era: a survey
The concept of event processing is established as a generic computational paradigm in
various application fields. Events report on state changes of a system and its environment …
various application fields. Events report on state changes of a system and its environment …
Time series data imputation: A survey on deep learning approaches
C Fang, C Wang - arXiv preprint arXiv:2011.11347, 2020 - arxiv.org
Time series are all around in real-world applications. However, unexpected accidents for
example broken sensors or missing of the signals will cause missing values in time series …
example broken sensors or missing of the signals will cause missing values in time series …
Autoencoders for improving quality of process event logs
Low quality of business process event logs, as determined by anomalous and missing
values, is often unavoidable in practical contexts. The output of process analysis that uses …
values, is often unavoidable in practical contexts. The output of process analysis that uses …
Efficient and effective data imputation with influence functions
Data imputation has been extensively explored to solve the missing data problem. The
dramatically rising volume of missing data makes the training of imputation models …
dramatically rising volume of missing data makes the training of imputation models …
Cleaning structured event logs: A graph repair approach
Event data are often dirty owing to various recording conventions or simply system errors.
These errors may cause many serious damages to real applications, such as inaccurate …
These errors may cause many serious damages to real applications, such as inaccurate …
Data dependencies extended for variety and veracity: A family tree
Besides the conventional schema-oriented tasks, data dependencies are recently revisited
for data quality applications, such as violation detection, data repairing and record matching …
for data quality applications, such as violation detection, data repairing and record matching …
Efficient alignment between event logs and process models
W Song, X Xia, HA Jacobsen… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
The aligning of event logs with process models is of great significance for process mining to
enable conformance checking, process enhancement, performance analysis, and trace …
enable conformance checking, process enhancement, performance analysis, and trace …
Sampling for big data profiling: A survey
Z Liu, A Zhang - IEEE access, 2020 - ieeexplore.ieee.org
Due to the development of internet technology and computer science, data is exploding at
an exponential rate. Big data brings us new opportunities and challenges. On the one hand …
an exponential rate. Big data brings us new opportunities and challenges. On the one hand …
IoT data quality
Data quality issues have been widely recognized in IoT data, and prevent the downstream
applications. In this tutorial, we review the state-of-the-art techniques for IoT data quality …
applications. In this tutorial, we review the state-of-the-art techniques for IoT data quality …
Efficiently cleaning structured event logs: a graph repair approach
Event data are often dirty owing to various recording conventions or simply system errors.
These errors may cause serious damage to real applications, such as inaccurate …
These errors may cause serious damage to real applications, such as inaccurate …