Journal of Intelligent Information Systems

Papers
(The H4-Index of Journal of Intelligent Information Systems is 20. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-06-01 to 2025-06-01.)
ArticleCitations
Predicting temporary deal success with social media timing signals53
A semiautomatic method for obtaining a predictive deep learning model and a rule-based system for abdominal aortic aneurysms48
Persuasive explanations for path reasoning recommendations46
News dissemination: a semantic approach to barrier classification46
Explaining the impact of design choices on model quality in predictive process monitoring45
Leveraging neighborhood and path information for influential spreaders recognition in complex networks40
MhSa-GRU: combining user’s dynamic preferences and items’ correlation to augment sequence recommendation39
Entity-aware answer sentence selection for question answering with transformer-based language models36
Correction to: Evaluating user story quality with LLMs: a comparative study31
Depression detection from sMRI and rs-fMRI images using machine learning30
Exploring rich structure information for aspect-based sentiment classification29
MYRTO: An efficient pervasive method for hybrid ML-based data filtered allocations28
Fake news detection based on statement conflict26
MF-EDNet: predicting stock market sector indices based on multi-feature fusion under emergency events25
Leveraging contextual embeddings and self-attention neural networks with bi-attention for sentiment analysis23
Impact of techniques to reduce error in high error rule-based expert system gradient descent networks23
Deep learning approaches to lexical simplification: A survey23
Clustering of renewable energy assets to optimize resource allocation and operational strategies22
Analyzing and improving stability of matrix factorization for recommender systems22
Temporal knowledge graph completion based on product space and contrastive learning of commonsense22
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