Browsing Faculty of Engineering and Science by Journals "Lecture Notes in Computer Science (LNCS)"
Now showing items 1-7 of 7
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Big Data Analytics Affordances for Social Innovation: A Theoretical Framework
(Journal article; Peer reviewed, 2021) -
Ecosystem of Social Media Listening Practices for Crisis Management
(Peer reviewed; Journal article, 2021)The benefits of using social media data as a source of information are recognized by both practice and research in crisis management. However, the existing understanding on the matter is fragmented, it oscillates between ... -
Exploring Multilingual Word Embedding Alignments in BERT Models: A Case Study of English and Norwegian
(Chapter; Peer reviewed, 2023)Contextual language models, such as transformers, can solve a wide range of language tasks ranging from text classification to question answering and machine translation. Like many deep learning models, the performance ... -
The Hierarchical Discrete Learning Automaton Suitable for Environments with Many Actions and High Accuracy Requirements
(Peer reviewed; Journal article, 2022)Since its early beginning, the paradigm of Learning Automata (LA), has attracted much interest. Over the last decades, new concepts and various improvements have been introduced to increase the LA’s speed and accuracy, ... -
How Quickly Can We Predict Users’ Ratings on Aesthetic Evaluations of Websites? Employing Machine Learning on Eye-Tracking Data
(Journal article; Peer reviewed, 2020) -
A Learning-Automata Based Solution for Non-equal Partitioning: Partitions with Common GCD Sizes
(Lecture Notes in Computer Science;12799, Peer reviewed; Journal article, 2021)The Object Migration Automata (OMA) has been used as a powerful tool to resolve real-life partitioning problems in random Environments. The virgin OMA has also been enhanced by incorporating the latest strategies in Learning ... -
Towards a deep reinforcement learning approach for Tower Line Wars
(Lecture Notes in Artificial Intelligence (LNAI), Journal article; Peer reviewed, 2017)There have been numerous breakthroughs with reinforcement learning in the recent years, perhaps most notably on Deep Reinforcement Learning successfully playing and winning relatively advanced computer games. There is ...