This paper is an extended version of a paper to be published in "MoDELS '21: ACM/IEEE 24th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings". It was presented at the 3rd Workshop on Artificial Intelligence and Model-driven Engineering
DoctorData stream clustering is an unsupervised learning method for sequential data. The data stream...
The following full text is a publisher's version. For additional information about this publica...
International audienceThis paper focuses on using feature salience to evaluate the quality of a part...
This paper is an extended version of a paper to be published in "ACM/IEEE 23rd International Confere...
Accompanying presentation to the main track paper "Detecting Quality Problems in Research Data: A Mo...
Analysis of Data quality is an important issue which has been addressed as data warehousing, data mi...
We propose the use of clustering methods in order to discover the quality of each element in a train...
Accompanying poster to the main track paper "Detecting Quality Problems in Research Data: A Model-Dr...
Electrical disturbances can have an adverse affect on people, businesses and other systems, and incr...
Clustering is a popular type of unsupervised learning technique that performs natural groupings on s...
The purpose of this research was to explore a systematic pattern for selecting quality tools and tec...
In this paper, we present the application of a clustering algorithm to exploit lexical and syntactic...
In this paper, we present the application of a clustering algorithm to exploit lexical and syntactic...
Identifying the root cause of an error in software testing is a demanding task. It becomes even hard...
Manufacturing process development is under constant pressure to achieve a good yield for stable proc...
DoctorData stream clustering is an unsupervised learning method for sequential data. The data stream...
The following full text is a publisher's version. For additional information about this publica...
International audienceThis paper focuses on using feature salience to evaluate the quality of a part...
This paper is an extended version of a paper to be published in "ACM/IEEE 23rd International Confere...
Accompanying presentation to the main track paper "Detecting Quality Problems in Research Data: A Mo...
Analysis of Data quality is an important issue which has been addressed as data warehousing, data mi...
We propose the use of clustering methods in order to discover the quality of each element in a train...
Accompanying poster to the main track paper "Detecting Quality Problems in Research Data: A Model-Dr...
Electrical disturbances can have an adverse affect on people, businesses and other systems, and incr...
Clustering is a popular type of unsupervised learning technique that performs natural groupings on s...
The purpose of this research was to explore a systematic pattern for selecting quality tools and tec...
In this paper, we present the application of a clustering algorithm to exploit lexical and syntactic...
In this paper, we present the application of a clustering algorithm to exploit lexical and syntactic...
Identifying the root cause of an error in software testing is a demanding task. It becomes even hard...
Manufacturing process development is under constant pressure to achieve a good yield for stable proc...
DoctorData stream clustering is an unsupervised learning method for sequential data. The data stream...
The following full text is a publisher's version. For additional information about this publica...
International audienceThis paper focuses on using feature salience to evaluate the quality of a part...
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