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Data Mining and Knowledge Discovery

Data Mining and Knowledge Discovery OnlineFirst articles

17.06.2019 Open Access

A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates

Our hypothesis is that building ensembles of small sets of strong classifiers constructed with different learning algorithms is, on average, the best approach to classification for real-world problems. We propose a simple mechanism for building …

13.06.2019 Open Access

More for less: adaptive labeling payments in online labor markets

In many predictive tasks where human intelligence is needed to label training instances, online crowdsourcing markets have emerged as promising platforms for large-scale, cost-effective labeling. However, these platforms also introduce significant …

01.06.2019 Open Access

Efficient mixture model for clustering of sparse high dimensional binary data

Clustering is one of the fundamental tools for preliminary analysis of data. While most of the clustering methods are designed for continuous data, sparse high-dimensional binary representations became very popular in various domains such as text …


HHMF: hidden hierarchical matrix factorization for recommender systems

Matrix factorization (MF) is one of the most powerful techniques used in recommender systems. MF models the (user, item) interactions behind historical explicit or implicit ratings. Standard MF does not capture the hierarchical structural …

25.04.2019 Open Access

Robust active attacks on social graphs

In order to prevent the disclosure of privacy-sensitive data, such as names and relations between users, social network graphs have to be anonymised before publication. Naive anonymisation of social network graphs often consists in deleting all …

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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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