Microbiome and metabolome contain information about host disease. Therefore, a multi-omics analysis of these data types can provide key constraints for disease classification. However, due to multi-omics data’s complex and high-dimensional nature, ...

Data integration combines information from different sources to provide a comprehensive view for making informed business decisions. The ETL (Extract, Transform, and Load) process is essential in data integration. In the past two decades, modeling ...

Data for several applications in diverse fields can be represented as multiple matrices that are linked across rows or columns. This is particularly common in molecular biomedical research, in which multiple molecular “omics” technologies may ...

Entity resolution is a key task in data integration and fusion, aiming to find all records describing the same real-world entity from multiple data sources. Blocking is an important step in entity resolution tasks to address the secondary time ...

Question Answering (QA) systems provide accurate answers to questions; however, they lack the ability to consolidate data from multiple sources, making it difficult to manage complex questions that could be answered with additional data retrieved ...

Deep Generative Models (DGMs) are becoming instrumental for inferring probability distributions inherent to complex processes, such as most questions in biomedical research. For many years, there was a lack of mathematical methods that would ...

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• Deep generative models propose a latent probability distribution to explain the data.
• Deep generative models rely on abundant data and good task definition.
• Deep generative models expand integrative single-cell -omics data ...

Social media has been fuelling necessary research in different areas, including the large-scale study of urban societies. Most research is done with a single source of information. Integrating data from multiple sources provides several benefits; ...

• Integration solution from the perspective of venues that improves state-of-the-art.
• Group of users integration solution; no other effort in this direction was found.
• Integration solution based on the activity performed by users in ...

Data integration plays a crucial role in business intelligence, aiding decision-makers by consolidating data from heterogeneous sources to provide deep insights into business operations and performance. In the big data era, automated data ...

• This study designs and instantiates a goal-driven data integration framework for data analytics.
• The proposed innovative design automates data integration for non-technical data users.
• Our artifact shows promising performance in ...

The deteriorating air quality in urban areas, particularly in developing countries, has led to increased attention being paid to the issue. Daily reports of air pollution are essential to effectively manage public health risks. Pollution ...

Digital revolution produces massive, heterogeneous and isolated data. These latter remain underutilized, unsuitable for integrated querying and knowledge discovering. Hence the importance of this survey on data integration which identifies challenging ...

Machine learning (ML) applications in medical artificial intelligence (AI) systems have shifted from traditional and statistical methods to increasing application of deep learning models. This survey navigates the current landscape of multimodal ...

Environmental flow (e-flow) decision making relies on flow-ecology models to predict ecological outcomes under different flow regimes. While expert knowledge has traditionally informed these models, there is increasing use of data-driven ...

• Exploration of a method to incorporate monitoring data into expert-opinion built Bayesian CPNs.
• Synthetic data records of varying characteristics were used to assess impact on model outcomes.
• Demonstrate that complementary use of ...

Entity Resolution (ER) constitutes a core data integration task that relies on Blocking in order to tame its quadratic time complexity. Schema-agnostic blocking achieves very high recall, requires no domain knowledge and applies to data of any ...

• Formalization of meta-blocking as a probabilistic classification task.
• A supervised meta-blocking algorithm that requires only 50 examples for training.
• Four new weighting schemes that enhance the meta-blocking performance.
• ...

We introduce a learning framework for the problem of unifying conflicting data in multiple records referring to the same entity—we call this problem “record fusion.” Record fusion generalizes two known problems: “data fusion” and “golden record.” Our ...

Problem statement

Record fusion involves merging duplicate records from different sources into a single, unified record. It helps to improve data quality, reduce redundancy, and enable more accurate analysis and decision-making. However, the ...

Data integration is the process of extracting information from multiple sources and jointly analyzing different data sets. In this paper, we propose to use the mixed ${\ell }_{2,1}$ regularized composite quasi-likelihood function to perform multi-task ...

Knowledge graphs are an increasingly popular choice for integrating heterogeneous data that have been collected independently from multiple sources. In many scenarios, including research and industry collaborations, the source data can be provided ...

State-of-the-art Entity Matching approaches rely on transformer architectures, such as BERT, for generating highly contextualized embeddings of terms. The embeddings are then used to predict whether pairs of entity descriptions refer to the same ...

Semantic schema alignment aims to match elements across a pair of schemas based on their semantic representation. It is a key primitive for data integration that facilitates the creation of a common data fabric across heterogeneous data sources. ...$$$$

There is an increasing awareness of the potential that our own self-gathered personal information has for our wellness and our health. This is partly because of our increasing awareness of what others – the major internet companies mainly – have ...

The rapid advancement of high-throughput technologies in the biomedical field has resulted in the accumulation of diverse omics data types, such as mRNA expression, DNA methylation, and microRNA expression, for studying various ...

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• Proposed method distinguishes long and short-term breast and kidney cancer survivors.
• Knowledge distillation-based VAE enables the utilization of all modalities.
• Predicting disease progression leads to more personalized and ...