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Langseth, Helge Author

Parameter learning in object-oriented Bayesian networks

  • Langseth H.
  • Bangsø O.

Annals of Mathematics and Artificial Intelligence - 1/12/2001

10.1023/a:1016769618900

Cite count: 27 (Scopus)
  • SJR Quartile: Q2
  • CiteScore: 2.5 (2020)
  • SJR: 0.747 (2001
  • SNIP: 1.542 (2001
  • SJR Categories: Applied Mathematics (Q2); Artificial Intelligence (Q2)

Effective hate-speech detection in Twitter data using recurrent neural networks

  • Pitsilis G.
  • Ramampiaro H.
  • Langseth H.

APPLIED INTELLIGENCE - 1/12/2018

10.1007/s10489-018-1242-y

Cite count: 67 (Scopus)
  • SJR Quartile: Q2
  • JCR Impact Factor: 2.882 (2018)
  • CiteScore: 6.8 (2020)
  • SJR: 0.651 (2018
  • SNIP: 1.585 (2018
  • JCR 5-year Impact Factor: 2.712
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q2)

Application of data-driven models in the analysis of marine power systems

  • Swider A.
  • Langseth H.
  • Pedersen E.

Applied Ocean Research - 1/11/2019

10.1016/j.apor.2019.101934

Cite count: 4 (Web of Science) 3 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.753 (2019)
  • CiteScore: 4.5 (2020)
  • SJR: 1.288 (2019
  • SNIP: 2.113 (2019
  • JCR 5-year Impact Factor: 2.935
  • JCR Categories: ENGINEERING, OCEAN
  • SJR Categories: Ocean Engineering (Q1)

The SACSO methodology for troubleshooting complex systems

  • Jensen F.
  • Kjærulff U.
  • Kristiansen B.
  • Langseth H.
  • Skaanning C.
  • Vomlel J.
  • Vomlelová M.
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Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM - 1/9/2001

10.1017/s0890060401154065

Cite count: 55 (Scopus)
  • SJR Quartile: Q1
  • CiteScore: 2.9 (2020)
  • SJR: 0.365 (2001
  • SNIP: 0.885 (2001
  • SJR Categories: Industrial and Manufacturing Engineering (Q1); Artificial Intelligence (Q3)
Open Access

Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation

  • Vassøy B.
  • Langseth H.

Artificial Intelligence Review - 1/4/2024

10.1007/s10462-023-10663-5

Cite count:
  • CiteScore: 23 (2022)
  • SJR: 2.49 (2022
  • SNIP: 4.347 (2022
Open Access

What predicts citation counts and translational impact in headache research? A machine learning analysis

  • Danelakis A.
  • Langseth H.
  • Nachev P.
  • Nelson A.
  • Bjørk M.H.
  • Matharu M.S.
  • Tronvik E.
  • May A.
  • Stubberud A.
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Cephalalgia : an international journal of headache - 1/5/2024

10.1177/03331024241251488

Cite count:

Scalable learning of probabilistic latent models for collaborative filtering

  • Langseth H.
  • Nielsen T.

Decision Support Systems - 1/6/2015

10.1016/j.dss.2015.03.006

Cite count: 16 (Web of Science) 15 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.604 (2015)
  • CiteScore: 10.5 (2020)
  • SJR: 1.87 (2015
  • SNIP: 2.284 (2015
  • JCR 5-year Impact Factor: 3.271
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Arts and Humanities (miscellaneous) (Q1); Developmental and Educational Psychology (Q1); Information Systems (Q1); Information Systems and Management (Q1); Management Information Systems (Q1)
Open Access

Probabilistic Models with Deep Neural Networks

  • Andrés R. Masegosa
  • Rafael Cabañas De Paz
  • Helge Langseth
  • Thomas Dyhre Nielsen
  • Antonio Salmerón Cerdán

Entropy - 1/01/2021

10.3390/e23010117

Cite count: 4 (Web of Science)
  • JCR Quartile: Q2 (2021)
  • JCR Impact Factor: 2.738 (2022)
  • Category normalized Impact: 0.156 (2021)
  • CiteScore: 4 (2020)
  • SJR: 0.468 (2020
  • SNIP: 1.059 (2020
  • JCR 5-year Impact Factor: 2.642
  • JCR Categories: PHYSICS, MULTIDISCIPLINARY

Frontiers in Artificial Intelligence and Applications: Preface

  • Kofod-Petersen A.
  • Heintz F.
  • Langseth H.

Frontiers in Artificial Intelligence and Applications - 1/1/2011

Cite count:
  • SJR Quartile: Q3
  • CiteScore: 0.6 (2020)
  • SJR: 0.246 (2011
  • SNIP: 0.583 (2011
  • SJR Categories: Artificial Intelligence (Q3)

Deep Contextual Grid Triplet Network for Context-Aware Recommendation

  • Sofia Aftab
  • Heri Ramampiaro
  • Helge Langseth
  • Massimiliano Ruocco

IEEE Access - 1/1/2023

10.1109/access.2023.3310470

Cite count:

Learning hybrid bayesian networks using mixtures of truncated basis functions. Aprendizaje de redes bayesianas híbridas con mixturas de funciones base truncadas

  • Inmaculada Pérez-Bernabé
  • Antonio Salmerón Cerdán
  • Helge Langseth

2015

Cite count:
  • Dialnet

Bayesian networks in reliability: The good, the bad, and the ugly

  • Langseth H.

Advances in Mathematical Modeling for Reliability - 1/5/2008

Cite count: 14 (Scopus)

Applications of Bayesian networks in reliability analysis

  • Langseth H.
  • Portinale L.

Bayesian Network Technologies: Applications and Graphical Models - 1/12/2007

10.4018/978-1-59904-141-4.ch005

Cite count: 7 (Scopus)

Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

Proceedings of the Sixth European Workshop on Probabilistic Graphical Models - 1/12/2012

Cite count: 11 (Scopus)
  • SJR Categories: Statistics and Probability

Extended abstract: Combining CBR and BN using metareasoning

  • Houeland T.
  • Bruland T.
  • Aamodt A.
  • Langseth H.

Frontiers in Artificial Intelligence and Applications - 1/1/2011

10.3233/978-1-60750-754-3-189

Cite count: 1 (Scopus)
  • SJR Quartile: Q3
  • CiteScore: 0.6 (2020)
  • SJR: 0.246 (2011
  • SNIP: 0.583 (2011
  • SJR Categories: Artificial Intelligence (Q3)

Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches

  • Tiwari, Shweta
  • Bell, Gavin
  • Langseth, Helge
  • Ramampiaro, Heri
  • Rocha, AP
  • Steels, L
  • VandenHerik, J
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ICAART: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE - VOL 3 - 2022

10.5220/0010991800003116

Financial Data Analysis with PGMs Using AMIDST

  • Cabanas R.
  • Martinez A.
  • Masegosa A.
  • Ramos-Lopez D.
  • Sameron A.
  • Nielsen T.
  • Langseth H.
  • Madsen A.
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IEEE International Conference on Data Mining Workshops, ICDMW - 30/01/2017

10.1109/icdmw.2016.0185

Cite count: 4 (Web of Science) 4 (Scopus)
  • Category normalized Impact: 0.586 (2017)
  • SJR Categories: Computer Science Applications; Software

Effects of data cleansing on load prediction algorithms

  • Hoverstad B.
  • Tidemann A.
  • Langseth H.

IEEE Symposium on Computational Intelligence Applications in Smart Grid, CIASG - 16/12/2013

10.1109/ciasg.2013.6611504

Cite count: 11 (Scopus)
  • SJR Categories: Artificial Intelligence; Computational Theory and Mathematics; Computer Networks and Communications; Computer Science Applications

Effects of scale on load prediction algorithms

  • Tidemann A.
  • Høverstad B.
  • Langseth H.
  • Öztürk P.

IET Conference Publications - 1/12/2013

10.1049/cp.2013.1116

Cite count: 7 (Scopus)
  • SJR Categories: Electrical and Electronic Engineering
Open Access

Architectures integrating case-based reasoning and Bayesian networks for clinical decision support

  • Bruland T.
  • Aamodt A.
  • Langseth H.

IFIP Advances in Information and Communication Technology - 1/1/2010

10.1007/978-3-642-16327-2-13

Cite count: 17 (Scopus)
  • SJR Quartile: Q4
  • CiteScore: 1 (2020)
  • SJR: 0.142 (2010
  • SNIP: 0.273 (2010
  • SJR Categories: Computer Networks and Communications (Q4); Information Systems (Q4); Information Systems and Management (Q4)

A hybrid CBR and BN architecture refined through data analysis

  • Bruland T.
  • Aamodt A.
  • Langseth H.

International Conference on Intelligent Systems Design and Applications, ISDA - 1/12/2011

10.1109/isda.2011.6121773

Cite count: 4 (Scopus)
  • SJR Categories: Artificial Intelligence; Computer Science Applications; Control and Systems Engineering; Signal Processing
Open Access

Mixtures of truncated basis functions

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING - 1/2/2012

10.1016/j.ijar.2011.10.004

Cite count: 56 (Web of Science) 55 (Scopus)
  • JCR Quartile: Q2 (2012)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.729 (2012)
  • Category normalized Impact: 1.763 (2012)
  • CiteScore: 7.1 (2020)
  • SJR: 1.494 (2012
  • SNIP: 2.132 (2012
  • JCR 5-year Impact Factor: 2.165
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)
Open Access

d-VMP: Distributed Variational Message Passing

  • Andres Masegosa
  • Ana M. Martinez
  • Helge Langseth
  • Thomas Dyhre Nielsen
  • Antonio Salmerón
  • Darío Ramos-López
  • Anders Læsø Madsen
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JMLR Workshop and Conference Proceedings - 1/1/2016

Cite count: 8 (Scopus)
  • JCR Impact Factor: 5 (2016)
  • CiteScore: 6.8 (2020)
  • SJR: 1.29 (2016
  • SNIP: 2.222 (2016
  • JCR 5-year Impact Factor: 7.649
  • JCR Categories: AUTOMATION & CONTROL SYSTEMS
Open Access

Learning to rank for personalised fashion recommender systems via implicit feedback

  • Nguyen H.
  • Almenningen T.
  • Havig M.
  • Schistad H.
  • Kofod-Petersen A.
  • Langseth H.
  • Ramampiaro H.
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 1/1/2014

10.1007/978-3-319-13817-6_6

Cite count: 11 (Scopus)
  • CiteScore: 1.8 (2020)
  • SJR: 0.354 (2014
  • SNIP: 0.753 (2014

This author has no patents.

This author has no reports or other types of publications.

Scopus: 18

Web of Science: 12

Scopus: 33

Web of Science: 13

Last data update: 5/18/24 9:32 AM
Next scheduled update: 5/25/24 3:00 AM