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Data Mining and Knowledge Discovery

Data Mining and Knowledge Discovery OnlineFirst articles

21-09-2020 Open Access

For real: a thorough look at numeric attributes in subgroup discovery

Subgroup discovery (SD) is an exploratory pattern mining paradigm that comes into its own when dealing with large real-world data, which typically involves many attributes, of a mixture of data types. Essential is the ability to deal with numeric …


Recency-based sequential pattern mining in multiple event sequences

The standard sequential pattern mining scheme hardly considers the positions of events in a sequence, and therefore it is difficult to focus on more interesting patterns that represent better the causal relationships between events. Without …

09-09-2020 Open Access

Online summarization of dynamic graphs using subjective interestingness for sequential data

Many real-world phenomena can be represented as dynamic graphs, i.e., networks that change over time. The problem of dynamic graph summarization, i.e., to succinctly describe the evolution of a dynamic graph, has been widely studied. Existing …

08-09-2020 Open Access

DeepTable: a permutation invariant neural network for table orientation classification

Tables are a common way to present information in an intuitive and concise manner. They are used extensively in media such as scientific articles or web pages. Automatically analyzing the content of tables bears special challenges. One of the most …


InceptionTime: Finding AlexNet for time series classification

This paper brings deep learning at the forefront of research into time series classification (TSC). TSC is the area of machine learning tasked with the categorization (or labelling) of time series. The last few decades of work in this area have …

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About this journal

The premier technical publication in the field, Data Mining and Knowledge Discovery is a resource collecting relevant common methods and techniques and a forum for unifying the diverse constituent research communities.

The journal publishes original technical papers in both the research and practice of data mining and knowledge discovery, surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications.

Coverage includes:

- Theory and Foundational Issues

- Data Mining Methods

- Algorithms for Data Mining

- Knowledge Discovery Process

- Application Issues.

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