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Machine Learning and Knowledge Extraction, Volume 3, Issue 1

March 2021 - 14 articles

Cover Story: We focus on the main challenges in AI system engineering along the development cycle of machine learning systems including lessons learned from past and ongoing research. This will be done by taking into account intrinsic conditions of deep learning models, data and software quality issues, and human-centered artificial intelligence (AI) postulates, including confidentiality and ethical aspects. The analysis outlines a fundamental theory-practice gap that superimposes the challenges of AI system engineering at the level of data quality assurance, model building, software engineering, and deployment. The aim of this paper is to pinpoint research topics relevant for AI system engineering by exploring approaches and challenges particularly posed by data quality assurance, embedded AI, confidentiality-preserving transfer learning, human–AI teaming, and ethics by design. View this paper
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Articles (14)

  • Perspective
  • Open Access
33 Citations
8,075 Views
15 Pages

Technological progress has led to powerful computers and communication technologies that penetrate nowadays all areas of science, industry and our private lives. As a consequence, all these areas are generating digital traces of data amounting to big...

  • Article
  • Open Access
5 Citations
5,197 Views
21 Pages

Idioms are multi-word expressions whose meaning cannot always be deduced from the literal meaning of constituent words. A key feature of idioms that is central to this paper is their peculiar mixture of fixedness and variability, which poses challeng...

  • Article
  • Open Access
6 Citations
5,328 Views
20 Pages

Automatic Feature Selection for Improved Interpretability on Whole Slide Imaging

  • Antoine Pirovano,
  • Hippolyte Heuberger,
  • Sylvain Berlemont,
  • SaÏd Ladjal and
  • Isabelle Bloch

Deep learning methods are widely used for medical applications to assist medical doctors in their daily routine. While performances reach expert’s level, interpretability (highlighting how and what a trained model learned and why it makes a specific...

  • Article
  • Open Access
48 Citations
7,981 Views
15 Pages

The most frequent faults in rotating electrical machines occur in their rolling element bearings. Thus, an effective health diagnosis mechanism of rolling element bearings is necessary from operational and economical points of view. Recently, convolu...

  • Article
  • Open Access
11 Citations
3,997 Views
23 Pages

This paper presents a novel on-the-fly, black-box, property-checking through learning approach as a means for verifying requirements of recurrent neural networks (RNN) in the context of sequence classification. Our technique steps on a tool for learn...

  • Article
  • Open Access
27 Citations
7,034 Views
35 Pages

Explainable AI Framework for Multivariate Hydrochemical Time Series

  • Michael C. Thrun,
  • Alfred Ultsch and
  • Lutz Breuer

The understanding of water quality and its underlying processes is important for the protection of aquatic environments. With the rare opportunity of access to a domain expert, an explainable AI (XAI) framework is proposed that is applicable to multi...

  • Article
  • Open Access
3 Citations
5,092 Views
49 Pages

Interpretable Topic Extraction and Word Embedding Learning Using Non-Negative Tensor DEDICOM

  • Lars Hillebrand,
  • David Biesner,
  • Christian Bauckhage and
  • Rafet Sifa

Unsupervised topic extraction is a vital step in automatically extracting concise contentual information from large text corpora. Existing topic extraction methods lack the capability of linking relations between these topics which would further help...

  • Article
  • Open Access
8 Citations
6,163 Views
28 Pages

Learning DOM Trees of Web Pages by Subpath Kernel and Detecting Fake e-Commerce Sites

  • Kilho Shin,
  • Taichi Ishikawa,
  • Yu-Lu Liu and
  • David Lawrence Shepard

The subpath kernel is a class of positive definite kernels defined over trees, which has the following advantages for the purposes of classification, regression and clustering: it can be incorporated into a variety of powerful kernel machines includi...

  • Article
  • Open Access
13 Citations
6,468 Views
11 Pages

Identifying fake news on media has been an important issue. This is especially true considering the wide spread of rumors on popular social networks such as Twitter. Various kinds of techniques have been proposed for automatic rumor detection. In thi...

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Mach. Learn. Knowl. Extr. - ISSN 2504-4990