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Langseth, Helge Author

A classification-based approach to monitoring the safety of dynamic systems

  • Zhong, Shengtong
  • Langseth, Helge
  • Nielsen, Thomas Dyhre

RELIABILITY ENGINEERING and SYSTEM SAFETY - 1/01/2014

10.1016/j.ress.2013.07.016

Cite count: 5 (Web of Science) 4 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.41 (2014)
  • CiteScore: 9.3 (2020)
  • SJR: 1.419 (2014
  • SNIP: 2.616 (2014
  • JCR 5-year Impact Factor: 2.693
  • JCR Categories: OPERATIONS RESEARCH & MANAGEMENT SCIENCE
  • SJR Categories: Applied Mathematics (Q1); Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q1)

A deep network model for paraphrase detection in short text messages

  • Agarwal B.
  • Ramampiaro H.
  • Langseth H.
  • Ruocco M.

INFORMATION PROCESSING and MANAGEMENT - 1/11/2018

10.1016/j.ipm.2018.06.005

Cite count: 55 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 3.892 (2018)
  • CiteScore: 8.6 (2020)
  • SJR: 1.043 (2018
  • SNIP: 3.011 (2018
  • JCR 5-year Impact Factor: 3.295
  • JCR Categories: INFORMATION SCIENCE & LIBRARY SCIENCE
  • SJR Categories: Computer Science Applications (Q1); Information Systems (Q1); Library and Information Sciences (Q1); Management Science and Operations Research (Q1); Media Technology (Q1)
Open Access

A latent model for collaborative filtering

  • Langseth H.
  • Nielsen T.

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING - 1/6/2012

10.1016/j.ijar.2011.11.002

Cite count: 23 (Web of Science) 31 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.729 (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)

AMIDST: A Java toolbox for scalable probabilistic machine learning

  • Masegosa A.
  • Martínez A.
  • Ramos-López D.
  • Cabañas R.
  • Salmerón A.
  • Langseth H.
  • Nielsen T.
  • Madsen A.
... View more Collapse

Knowledge-Based Systems - 1/01/2019

10.1016/j.knosys.2018.09.019

Cite count: 7 (Web of Science) 7 (Scopus)
  • JCR Quartile: Q1 (2019)
  • SJR Quartile: Q1
  • JCR Impact Factor: 5.921 (2022)
  • Category normalized Impact: 0.374 (2019)
  • CiteScore: 11.3 (2020)
  • SJR: 1.754 (2019
  • SNIP: 2.828 (2019
  • JCR 5-year Impact Factor: 6.075
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1); Information Systems and Management (Q1); Management Information Systems (Q1); Software (Q1)

Analysis of OREDA data for maintenance optimisation

  • Langseth H.
  • Haugen K.
  • Sandtorv H.

Reliability Engineering and System Safety - 1/1/1998

10.1016/s0951-8320(98)83003-2

Cite count: 18 (Scopus)
  • CiteScore: 9.3 (2020)

Analyzing concept drift: A case study in the financial sector

  • Masegosa A.R.
  • Martínez A.M.
  • Ramos-López D.
  • Langseth H.
  • Nielsen T.D.
  • Salmerón A.

Intelligent Data Analysis - 21/05/2020

10.3233/ida-194515

Cite count: 7 (Web of Science) 1 (Scopus)
  • JCR Quartile: Q4 (2020)
  • JCR Impact Factor: 0.86 (2022)
  • Category normalized Impact: 0.379 (2020)
  • CiteScore: 1.7 (2020)
  • SJR: 0.231 (2020
  • SNIP: 0.527 (2020
  • JCR 5-year Impact Factor: 0.894
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

A parallel algorithm for Bayesian network structure learning from large data sets

  • Madsen A.
  • Jensen F.
  • Salmerón A.
  • Langseth H.
  • Nielsen T.

KNOWLEDGE-BASED SYSTEMS - 1/2/2017

10.1016/j.knosys.2016.07.031

Cite count: 62 (Web of Science) 50 (Scopus)
  • JCR Quartile: Q1 (2017)
  • SJR Quartile: Q1
  • JCR Impact Factor: 4.396 (2022)
  • Category normalized Impact: 2.246 (2017)
  • CiteScore: 11.3 (2020)
  • SJR: 1.378 (2017
  • SNIP: 2.349 (2017
  • JCR 5-year Impact Factor: 4.514
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1); Information Systems and Management (Q1); Management Information Systems (Q1); Software (Q1)

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)

Applying Bayesian optimization to predict parameters in a time-domain model for cross-flow vortex-induced vibrations

  • Andersen M.L.
  • Sævik S.
  • Wu J.
  • Leira B.J.
  • Langseth H.

Marine Structures - 1/3/2024

10.1016/j.marstruc.2023.103571

Cite count:
  • CiteScore: 7.6 (2022)
  • SJR: 1.228 (2022
  • SNIP: 2.239 (2022
Open Access

A review of inference algorithms for hybrid Bayesian networks

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

JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH - 1/8/2018

10.1613/jair.1.11228

Cite count: 17 (Web of Science) 16 (Scopus)
  • JCR Quartile: Q3 (2018)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.82 (2022)
  • Category normalized Impact: 0.256 (2018)
  • CiteScore: 3.23 (2018)
  • SJR: 0.754 (2018
  • SNIP: 2.084 (2018
  • JCR 5-year Impact Factor: 2.448
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Artificial Intelligence (Q1)

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)

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)

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

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
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
... View more Collapse

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

Dynamic Bayesian modeling for risk prediction in credit operations

  • Borchani H.
  • Martínez A.
  • Masegosa A.
  • Langseth H.
  • Nielsen T.
  • Salmerón A.
  • Fernández A.
  • Madsen A.
  • Sáez R.
... View more Collapse

The 13th Scandinavian Conference on Artificial Intelligence (SCAI'2015) - 1/1/2015

10.3233/978-1-61499-589-0-17

Cite count: 4 (Web of Science) 4 (Scopus)
  • SJR Quartile: Q3
  • Category normalized Impact: 0.286 (2015)
  • CiteScore: 0.6 (2020)
  • SJR: 0.238 (2015
  • SNIP: 0.429 (2015
  • SJR Categories: Artificial Intelligence (Q3)

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

Extended abstract: A design for a tourist CF system

  • Lillegraven T.
  • Wolden A.
  • Kofod-Petersen A.
  • Langseth H.

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

10.3233/978-1-60750-754-3-193

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

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)
Open Access

Fast approximate inference in hybrid Bayesian networks using dynamic discretisation

  • Langseth H.
  • Marquez D.
  • Neil M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 23/10/2013

10.1007/978-3-642-38637-4_23

Cite count: 2 (Scopus)
  • CiteScore: 1.8 (2020)
  • SJR: 0.36 (2013
  • SNIP: 0.775 (2013

Financial Data Analysis with PGMs Using AMIDST

  • Cabanas R.
  • Martinez A.
  • Masegosa A.
  • Ramos-Lopez D.
  • Sameron A.
  • Nielsen T.
  • Langseth H.
  • Madsen A.
... View more Collapse

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

Forecasting intra-hour imbalances in electric power systems

  • Salem T.S.
  • Kathuria K.
  • Ramampiaro H.
  • Langseth H.

33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 - 1/1/2019

Cite count: 4 (Scopus)

Inter-session modeling for session-based recommendation

  • Ruocco M.
  • Skrede O.
  • Langseth H.

ACM International Conference Proceeding Series - 27/8/2017

10.1145/3125486.3125491

Cite count: 25 (Scopus)
  • SJR Categories: Ocean Engineering

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