International audienceThere is an increasing need to quickly understand the contents log data. A wide range of patterns can be computed and provide valuable information: for example existence of repeated sequences of events or periodic behaviors. However pattern mining techniques often produce many patterns that have to be examined one by one, which is time consuming for experts. On the other hand, visualization techniques are easier to understand , but cannot provide the in-depth understanding provided by pattern mining approaches. Our contribution is to propose a novel visual analytics method that allows to immediately visualize hidden structures such as repeated sets/sequences and periodicity, allowing to quickly gain a deep understandin...
National audienceThe context of this work is the study of sequential data that can be represented wi...
We present a set of techniques and design principles for the visualization of large dynamic software...
[[abstract]]Repeating patterns represent temporal relations among data items, which could be used fo...
International audienceThere is an increasing need to quickly understand the contents log data. A wid...
International audienceThe quantity of event logs available is increasing rapidly, be they produced b...
A sequential pattern in data mining is a finite series of elements such as A B C D where A, B, C,...
International audienceIn this paper we present a comprehensive log compression (CLC) method that use...
International audienceData mining techniques allow users to discover novelty in huge amounts of data...
Cyber security threat detection is the process of identifying anomalous and frequent patterns within...
International audienceDiscovering temporal patterns hidden in a sequence of events has applications ...
In the present-day, sensor data and textual logs are generated by many devices. Analysing these time...
Sequential pattern analysis targets on finding statistically relevant temporal structures where the ...
Analysing software log files has become a challenging task due to the diversity in file structure an...
Recently, with the constant progress in software and hardware technologies, real-world databases ten...
Abstract In this paper, we introduce a visual analytics approach aimed at helping machine learning e...
National audienceThe context of this work is the study of sequential data that can be represented wi...
We present a set of techniques and design principles for the visualization of large dynamic software...
[[abstract]]Repeating patterns represent temporal relations among data items, which could be used fo...
International audienceThere is an increasing need to quickly understand the contents log data. A wid...
International audienceThe quantity of event logs available is increasing rapidly, be they produced b...
A sequential pattern in data mining is a finite series of elements such as A B C D where A, B, C,...
International audienceIn this paper we present a comprehensive log compression (CLC) method that use...
International audienceData mining techniques allow users to discover novelty in huge amounts of data...
Cyber security threat detection is the process of identifying anomalous and frequent patterns within...
International audienceDiscovering temporal patterns hidden in a sequence of events has applications ...
In the present-day, sensor data and textual logs are generated by many devices. Analysing these time...
Sequential pattern analysis targets on finding statistically relevant temporal structures where the ...
Analysing software log files has become a challenging task due to the diversity in file structure an...
Recently, with the constant progress in software and hardware technologies, real-world databases ten...
Abstract In this paper, we introduce a visual analytics approach aimed at helping machine learning e...
National audienceThe context of this work is the study of sequential data that can be represented wi...
We present a set of techniques and design principles for the visualization of large dynamic software...
[[abstract]]Repeating patterns represent temporal relations among data items, which could be used fo...