> Detailanzeige

Park, Laurence A. F. [HerausgeberIn]; Gomes, Heitor Murilo [HerausgeberIn]; Doborjeh, Maryam [HerausgeberIn]; Boo, Yee Ling [HerausgeberIn]; Koh, Yun Sing [HerausgeberIn]; Zhao, Yanchang [HerausgeberIn]; Williams, Graham [HerausgeberIn]; Simoff, Simeon [HerausgeberIn]

Data Mining - [1st ed. 2022.]

Literatur-
verwaltung

Zur
Merkliste

Lösche von
Merkliste

Per Whatsapp teilen

Schließen

Merkliste



Sie können Bookmarks mittels Listen verwalten, loggen Sie sich dafür bitte in Ihr SLUB Benutzerkonto ein.
  • Medientyp: E-Book
  • Titel: Data Mining : 20th Australasian Conference, AusDM 2022, Western Sydney, Australia, December 12–15, 2022, Proceedings
  • Beteiligte: Park, Laurence A. F. [HerausgeberIn]; Gomes, Heitor Murilo [HerausgeberIn]; Doborjeh, Maryam [HerausgeberIn]; Boo, Yee Ling [HerausgeberIn]; Koh, Yun Sing [HerausgeberIn]; Zhao, Yanchang [HerausgeberIn]; Williams, Graham [HerausgeberIn]; Simoff, Simeon [HerausgeberIn]
  • Erschienen: Singapore: Springer Nature Singapore, 2022.
    Singapore: Imprint: Springer, 2022.
  • Erschienen in: Communications in Computer and Information Science ; 1741
  • Ausgabe: 1st ed. 2022.
  • Umfang: 1 Online-Ressource(XIII, 245 p. 82 illus., 78 illus. in color.)
  • Sprache: Englisch
  • DOI: 10.1007/978-981-19-8746-5
  • ISBN: 9789811987465
  • Identifikator:
  • Schlagwörter: Data mining. ; Artificial intelligence. ; Image processing—Digital techniques. ; Computer vision. ; Education—Data processing. ; Computer science—Mathematics.
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: Research Track -- Measuring Content Preservation in Textual Style Transfer -- A Temperature-Modified Dynamic Embedded Topic Model -- Measuring Difficulty of Learning using Ensembles Methods -- Graph Embeddings for Non-IID Data Feature Representation Learning -- Enhancing Understandability of Omics Data with SHAP, Embedding Projections and Interactive Visualisations -- WinDrift: Early Detction of Concept Drift through the use of Corresponding and Hierarchical Time Windows -- Investigation of Explainability Techniques for Multimodal Transformers -- Effective Imbalance Learning Utilizing Informative Data -- Interpretable Decision Tree via Human-In-The-Loop-Learning -- Application Track -- A Comparative Look at the Resilience of Discriminative and Generative Classifiers to Missing Data in Longitudinal Datasets -- Hierarchical Topic Model Inference by Community Discovery on Word Co-Occurrence Networks -- UMLS-Based Question-Answering Approach for Automatic Initial Frailty Assessment -- Natural Language Query For Technical Knowledge Graph Navigation -- Decomposition of Service Level Encoding for Anomaly Detcion -- Improving Ads-Profitability Using Traffic Fingerprints -- Attractiveness Analysis for Health Claims on Food Packages -- SchedmaDB: A Dataset for Structures in Relational Data.

    This book constitutes the refereed proceedings of the 20th Australasian Conference on Data Mining, AusDM 2022, held in Western Sydney, Australia, during December 12–15, 2022. The 17 full papers included in this book were carefully reviewed and selected from 44 submissions. They were organized in topical sections as research track and application track.