A similarity measure is a measure evaluating the degree of similarity between two fuzzy data sets and has become an essential tool in many applications including data mining, pattern recognition, and clustering. In this paper, we propose a similarity...
Similarity to reality is a necessary property of models in earth sciences. Similarity information can thus possess a large potential in advancing geophysical modeling and data assimilation. We present a formalism for utilizing similarity within the e...
In music, plagiarism has been an important but troubled issue, which becomes ever more critical with the widespread usage of generative AI tools. Meanwhile, the development of techniques for music similarity detection has been hampered by the scarcit...
To help users discover the most relevant spatial datasets in the ever-growing global spatial data infrastructures (SDIs), a number of similarity measures of geospatial data based on metadata have been proposed. Researchers have assessed the similarit...
Federated data spaces, established through initiatives such as IDSA and GAIA-X, enable organizations to share and monetize datasets under contractual terms. However, enforcing these contracts—particularly detecting unauthorized reuse or modific...
Federated learning (FL) offers a distributed approach for the collaborative training of machine learning models across decentralized clients while safeguarding data privacy. This characteristic makes FL well suited for privacy-sensitive fields such a...
Automatic Identification System (AIS) data have been widely used in many fields, such as collision detection, navigation, and maritime traffic management. Similarity analysis is an important process for most AIS trajectory analysis topics. However, m...
With the complexity of the task requirement, multiple operating conditions have gradually become the common scenario for equipment. However, the degradation trend of monitoring data cannot be accurately extracted in life prediction under multiple ope...
Continuous monitoring of patients involves collecting and analyzing sensory data from a multitude of sources. To overcome communication overhead, ensure data privacy and security, reduce data loss, and maintain efficient resource usage, the processin...
In multiview data clustering, consistent or complementary information in the multiview data can achieve better clustering results. However, the high dimensions, lack of labeling, and redundancy of multiview data certainly affect the clustering effect...
Shape similarity measurement model is often used to solve shape-matching problems in geospatial data matching. It is widely used in geospatial data integration, conflation, updating and quality assessment. Many shape similarity measurements apply onl...
The identification of cancer subtypes is crucial to cancer diagnosis and treatments. A number of methods have been proposed to identify cancer subtypes by integrating multi-omics data in recent years. However, the existing methods rarely consider the...
This paper proposes a spatial data attribute similarity measure method based on granular computing closeness. This method uses the distance and membership degree of different index levels of spatial entities to measure the similarity of attributes. I...
Currently, a significant focus has been established on the privacy protection of multi-dimensional data publishing in various application scenarios, such as scientific research and policy-making. The K-anonymity mechanism based on clustering is the m...
Many similarity measure algorithms of nodes in weighted graph data have been proposed by employing the degree of nodes in recent years. Despite these algorithms obtaining great results, there may be still some limitations. For instance, the strength...
The increasing computerisation of medical services has highlighted inconsistencies in the way in which patients’ historic medical data were recorded. Differences in process and practice between medical services and facilities have led to many i...
We propose an instance-based learning approach with data augmentation and similarity evaluation to estimate the remaining useful life (RUL) of a mechanical component for health management. The publicly available PRONOSTIA datasets, which provide acce...
Accurate streamflow modeling in data-scarce catchments remains a significant challenge due to the limited availability of historical records. Transfer Learning (TL), increasingly applied in hydrology, leverages knowledge from data-rich catchments (so...
The rate of penetration (ROP) is an important indicator affecting the drilling cost and drilling performance. Accurate prediction of the ROP has important guiding significance for increasing the drilling speed and reducing costs. Recently, numerous s...
In recent years, with the development of the Internet of Things (IoT) technology, a large amount of data can be captured from sensors for real-time analysis. By monitoring the traffic video data from the IoT, we can detect the anomalies that may occu...
Data stream mining techniques have recently received increasing research interest, especially in medical data classification. An unbalanced representation of the classification’s targets in these data is a common challenge because classificatio...
This paper aims to develop a novel method for the dynamic equivalence of a renewable power plant, ultimately contributing to power system modeling and enhancing the integration of renewable energy sources. In order to address the challenge posed by c...
In actual industrial scenarios, collecting a complete dataset with all fault categories under the same conditions is challenging, leading to a loss in fault category knowledge in single-source domains. Deep learning domain adaptation methods face dif...
Suffering from the well-known Hughes phenomenon, hyperspectral image (HSI) classification is still very challenging, which is mainly due to the high-dimensional features of HSIs and relatively limited training samples. To systematically represent the...
Detection of damages caused by natural disasters is a delicate and difficult task due to the time constraints imposed by emergency situations. Therefore, an automatic Change Detection (CD) algorithm, with less user interaction, is always very interes...
Joint inversion of gravity and gravity gradient data are of paramount importance in geophysical exploration, as the integration of these datasets enhances subsurface resolution and facilitates the accurate delineation of ore body shapes and boundarie...
The Internet of Things (IoT) and sensors are becoming increasingly popular, especially in monitoring large and ambient environments. Applications that embrace IoT and sensors often require mining the data feeds that are collected at frequent interval...
Background: The precise identification of cancer subtypes through the integration of multi-omics data has emerged as a key research direction in bioinformatics. Among existing multi-omics integration methods, similarity graph-based clustering algorit...
In this paper, we proposed methods to accurately predict pixel values by effectively using local similarity, curved surface characteristics, and edge characteristics present in an image. Furthermore, to hide more confidential data in a cover image us...
Reliability and safety are the most important indicators in the electric system. When a ground fault occurs, the electrical equipment and personnel will be greatly threatened. Due to the zero-sequence voltage/current sensor networks applied in the sy...
Semi-structured documents contain both hierarchical structure and field-level semantics. This makes similarity measurement difficult for methods that focus only on structure or only on global semantic representations. To address this problem, we prop...
We investigated how grammatical gender affects the way bilinguals perceive the similarity of an object. We adopted the Sapir–Whorf hypothesis regarding the effect of language on a person’s way of thinking. Different language characteristi...
Place types are often used to query places or retrieve data in gazetteers. Existing gazetteers do not use the same place type classification schemes, and the various typing schemes can cause difficulties in data alignment and matching. Different plac...
In modern biology and medicine, drug-drug similarity is a major task with various applications in pharmaceutical drug development. Various direct and indirect sources of evidence obtained from drug-centric data such as side effects, drug interactions...
Although NAND (Not And) flash-based Solid-State Drive (SSD) has recently demonstrated a significant performance advantage against hard disk, it still suffers from non-negligible performance under-utilization issues as the access conflict often occurs...
Sequence similarity searches have been widely used in the analyses of metagenomic sequencing data. Finding homologous sequences in a reference database enables the estimation of taxonomic and functional characteristics of each query sequence. Because...
Time series data typically exhibit high dimensionality and complexity, necessitating the use of specific approximation methods to perform computations on the data. The currently employed compression methods suffer from varying degrees of feature loss...
The rapid integration of Machine Learning (ML) in organizational practices has driven demand for substantial computational resources, incurring both high economic costs and environmental impact, particularly from energy consumption. This challenge is...
The mobility of nodes leads to dynamic changes in topology structure, which makes the traditional routing algorithms of a wireless network difficult to apply to the opportunistic network. In view of the problems existing in the process of information...
Patient similarity analytics has emerged as an essential tool to identify cohorts of patients who have similar clinical characteristics to some specific patient of interest. In this study, we propose a patient similarity measure called D3K that incor...
Multivariate data sets are common in various application areas, such as wireless sensor networks (WSNs) and DNA analysis. A robust mechanism is required to compute their similarity indexes regardless of the environment and problem domain. This study...
The amount of human action video data is increasing rapidly due to the growth of multimedia data, which increases the problem of how to process the large number of human action videos efficiently. Therefore, we devise a novel approach for human actio...
Graph visualization has been successfully applied in a wide range of problems and applications. Although different approaches are available to create visual representations, most of them suffer from clutter when faced with many nodes and/or edges. Am...
The increase in heterogeneous data in the building energy domain creates a difficult challenge for data integration. Schema matching, which maps the raw data from the building energy domain to a generic data model, is the necessary step in data integ...
The assessment of building-level flood damage in low-relief floodplains is constrained by pronounced exposure heterogeneity and a lack of object-level damage data. This study proposes a similarity-based fuzzy modeling framework for direct material fl...
In this paper, a novel building change detection approach is proposed using statistical region merging (SRM) and a shape context similarity model for Light Detection and Ranging (LiDAR) data. First, digital surface models (DSMs) are generated from Li...
Although data-independent acquisition (DIA) has the ability to identify and quantify all peptides in a sample, highly complex mixed mass spectra present difficulties for accurate peptide and protein identification. Additionally, the correspondence be...
There is a large risk of damage, triggered by harsh ocean environments, associated with offshore structures, so structural health monitoring plays an important role in preventing the occurrence of critical and global structural failure from such dama...
This paper presents a database that includes information on national recipes and their ingredients for 171 countries, measures for food taste similarities between all 171 countries as well as bilateral migration and agro-food trade data for 5 years....
This paper presents an approach to detecting patterns in a three-dimensional context, emphasizing the role played by the local geometry of the surface model. The core of the associated algorithm is represented by the cosine similarity computed to sub...
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