Search
Search Results
-
-
Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
-
DQMMBSC: design of an augmented deep Q-learning model for mining optimisation in IIoT via hybrid-bioinspired blockchain shards and contextual consensus
Single-chained blockchains are highly secure but cannot be scaled to larger IIoT (Internet of Industrial Things) network scenarios due to storage...
-
HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer...
-
Hierarchical adaptive evolution framework for privacy-preserving data publishing
The growing need for data publication and the escalating concerns regarding data privacy have led to a surge in interest in Privacy-Preserving Data...
-
Anomaly analytics in data-driven machine learning applications
Machine learning is used widely to create a range of prediction or classification models. The quality of the machine learning (ML) models depends not...
-
Temporal analysis of computational economics: a topic modeling approach
This study offers a comprehensive investigation into the thematic evolution within computational economics over the past two decades, leveraging...
-
Assessing the cooling impact of the urban park during pre- and post-cyclone using Landsat images
Cities are far warmer than their surroundings. Using vegetation is one of the best techniques to mitigate the effects of urban heat islands (UHI)....
-
Examining ALS: reformed PCA and random forest for effective detection of ALS
ALS (Amyotrophic Lateral Sclerosis) is a fatal neurodegenerative disease of the human motor system. It is a group of progressive diseases that...
-
Federated learning for digital healthcare: concepts, applications, frameworks, and challenges
Various hospitals have adopted digital technologies in the healthcare sector for various healthcare-related applications. Due to the effect of the...
-
MIM: A multiple integration model for intrusion detection on imbalanced samples
The quantity of normal samples is commonly significantly greater than that of malicious samples, resulting in an imbalance in network security data....
-
FlexpushdownDB: rethinking computation pushdown for cloud OLAP DBMSs
Modern cloud-native OLAP databases adopt a storage-disaggregation architecture that separates the management of computation and storage. A major...
-
Data reduction in big data: a survey of methods, challenges and future directions
Data reduction plays a pivotal role in managing and analyzing big data, which is characterized by its volume, velocity, variety, veracity, value,...
-
Unveiling the impact of employee-customer familiarity on customer purchase intentions: an empirical investigation within the realm of web-based date analytics
This research delves into the intricate dynamics of employee-customer familiarity and its profound influence on customer purchase intentions within...
-
Emotion AWARE: an artificial intelligence framework for adaptable, robust, explainable, and multi-granular emotion analysis
Emotions are fundamental to human behaviour. How we feel, individually and collectively, determines how humanity evolves and advances into our shared...
-
A Meta-learner approach to multistep-ahead time series prediction
The utilization of machine learning has become ubiquitous in addressing contemporary challenges in data science. Moreover, there has been significant...
-
Extract Implicit Semantic Friends and Their Influences from Bipartite Network for Social Recommendation
Social recommendation often incorporates trusted social links with user-item interactions to enhance rating prediction. Although methods that...
-
Open benchmark for filtering techniques in entity resolution
Entity Resolution identifies entity profiles that represent the same real-world object. A brute-force approach that considers all pairs of entities...
-
A robust hubness-based algorithm for image data stream classification
Image data stream classification is in high demand and can be used in various contexts, such as public security, medicine, and remote sensing....
-
Exploiting recurrent graph neural networks for suffix prediction in predictive monitoring
Predictive monitoring is a subfield of process mining that aims to predict how a running case will unfold in the future. One of its main challenges...
