Abstract. This paper studies concept drift over time. We first define the meaning of a concept in terms of intension, extension and label. We then introduce concept drift over time and two derived notions: (in)stability over a time period and concept shift between two time points. We apply our framework in three case-studies, one from communication science, on DBPedia, and one in the legal domain. We describe ways of identifying interesting changes in the meaning of concept within given application contexts. These case-studies illustrate the feasibility of our framework in analysing concept drift in knowledge organisation schemas of varying expressiveness.
Hinder F, Vaquet V, Brinkrolf J, Hammer B. Model-based explanations of concept drift. Neurocomputing...
This paper presents work in progress on an algorithm to track and identify changes in the vocabulary...
. Technical domains are affected by continuous change as a reflection of technological progress. Cor...
This paper studies concept drift over time. We first define the meaning of a concept in terms of int...
Semantic change and concept drift are studied in many differentacademic fields. Different domains ha...
We present an approach to estimating concept drift in online news. Our method is to construct tempor...
Abstract. The development and maintenance of Knowledge Organi-zation Systems (KOS) such as classific...
Concept drift primarily refers to an online supervised learning scenario when the relation between t...
Examining concepts that change over time has been an active area of research within data mining. Thi...
In the real world data is often non stationary. In predictive analytics, machine learning and data m...
Words change meaning over time. Some meaning shift is accompanied by a corresponding change in subje...
This paper addresses the task of learning concept descriptions from streams of data. As new data are...
Abstract. This paper addresses the task of learning concept descriptions from streams of data. As ne...
Building upon and extending existing work, this paper presents a framework for measuring semantic dr...
Examining concepts that change over time has been an active area of research within data mining. Thi...
Hinder F, Vaquet V, Brinkrolf J, Hammer B. Model-based explanations of concept drift. Neurocomputing...
This paper presents work in progress on an algorithm to track and identify changes in the vocabulary...
. Technical domains are affected by continuous change as a reflection of technological progress. Cor...
This paper studies concept drift over time. We first define the meaning of a concept in terms of int...
Semantic change and concept drift are studied in many differentacademic fields. Different domains ha...
We present an approach to estimating concept drift in online news. Our method is to construct tempor...
Abstract. The development and maintenance of Knowledge Organi-zation Systems (KOS) such as classific...
Concept drift primarily refers to an online supervised learning scenario when the relation between t...
Examining concepts that change over time has been an active area of research within data mining. Thi...
In the real world data is often non stationary. In predictive analytics, machine learning and data m...
Words change meaning over time. Some meaning shift is accompanied by a corresponding change in subje...
This paper addresses the task of learning concept descriptions from streams of data. As new data are...
Abstract. This paper addresses the task of learning concept descriptions from streams of data. As ne...
Building upon and extending existing work, this paper presents a framework for measuring semantic dr...
Examining concepts that change over time has been an active area of research within data mining. Thi...
Hinder F, Vaquet V, Brinkrolf J, Hammer B. Model-based explanations of concept drift. Neurocomputing...
This paper presents work in progress on an algorithm to track and identify changes in the vocabulary...
. Technical domains are affected by continuous change as a reflection of technological progress. Cor...