Blar i Institutt for datateknologi og informatikk på tidsskrift "Knowledge-Based Systems"

Viser treff 1-8 av 8

    • A Parallel Algorithm for Bayesian Network Structure Learning from Large Data Sets 

      Madsen, Anders L.; Jensen, Frank; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D. (Journal article; Peer reviewed, 2017)
      This paper considers a parallel algorithm for Bayesian network structure learning from large data sets. The parallel algorithm is a variant of the well known PC algorithm. The PC algorithm is a constraint-based algorithm ...

    • AMIDST: A Java toolbox for scalable probabilistic machine learning 

      Masegosa, Andres; Martinez, Ana M.; Ramos-López, Dario; Cabañas, Rafael; Langseth, Helge; Nielsen, Thomas D.; Madsen, Anders L. (Journal article; Peer reviewed, 2018)
      The AMIDST Toolbox is an open source Java software for scalable probabilistic machine learning with a special focus on (massive) streaming data. The toolbox supports a flexible modelling language based on probabilistic ...

    • AMIDST: A Java toolbox for scalable probabilistic machine learning 

      Masegosa, Andres; Martinez, Ana M.; Ramos-López, Dario; Cabañas, Rafael; Salmeron, Antonio; Langseth, Helge; Nielsen, Thomas D. (Journal article; Peer reviewed, 2019)

    • Distribution and gradient constrained embedding model for zero-shot learning with fewer seen samples 

      Zhang, Jing; Geng, YangLi-ao; Wang, Wen; Sun, Wenju; Yang, Zhirong; Li, Qingyong (Peer reviewed; Journal article, 2022)
      Zero-Shot Learning (ZSL), which aims to recognize unseen classes with no training data, has made great progress in recent years. However, established ZSL methods implicitly assumed that there exist sufficient labeled samples ...

    • High Utility Drift Detection in Quantitative Data Streams 

      Duong, Quang-Huy; Ramampiaro, Heri; Nørvåg, Kjetil; Fournier-Viger, Philippe; Dam, Thu-Lan (Journal article; Peer reviewed, 2018)
      This paper presents an efficient algorithm for detecting changes (drifts) in the utility distributions of patterns, named High Utility Drift Detection in Transactional Data Stream (HUDD-TDS). The algorithm is specifically ...

    • Online grooming detection: A comprehensive survey of child exploitation in chat logs 

      Rezaee Borj, Parisa; Raja, Kiran; Bours, Patrick Adrianus (Peer reviewed; Journal article, 2022)
      Social media platforms present significant threats against underage users targeted for predatory intents. Many early research works have applied the footprints left by online predators to investigate online grooming. While ...

    • Predicting missing pairwise preferences from similarity features in group decision making 

      Abolghasemi, Roza; Khadka, Rabindra; Lind, Pedro; Engelstad, Paal E.; Viedma, Enrique Herrera; Yazidi, Anis (Peer reviewed; Journal article, 2022)
      In group decision-making (GDM), fuzzy preference relations (FPRs) refer to pairwise preferences in the form of a matrix. Within the field of GDM, the problem of estimating missing values is of utmost importance, since many ...

    • Towards efficiently mining closed high utility itemsets from incremental databases 

      Dam, Thu-Lan; Ramampiaro, Heri; Nørvåg, Kjetil; Duong, Quang-Huy (Journal article; Peer reviewed, 2018)
      The set of closed high-utility itemsets (CHUIs) concisely represents the exact utility of all itemsets. Yet, it can be several orders of magnitude smaller than the set of all high-utility itemsets. Existing CHUI mining ...