Relying on user-generated content narrating individual experiences and personalized contextualization of location-specific realities, this study introduced a novel methodological approach and analysis tool that can aid health informatics in understan...
Today, data are no longer confined to numerical values arranged in row-by-column matrices or stored neatly within relational databases. One of the defining characteristics of big data is its high variety, encompassing unstructured and multimodal form...
15 October 2024
There has been a growing emphasis on data across various health-related fields, not just in nursing research, due to the increasing volume of unstructured data in electronic health records (EHRs). Natural Language Processing (NLP) provides a solution...
Extract, Transform, and Load (ETL) and Online Analytical Processing (OLAP) provide robust mechanisms for integrating structured data and supporting multidimensional analysis. Still, they offer limited support for semantic access to unstructured textu...
Manufacturing companies face significant challenges in leveraging artificial intelligence for equipment management due to high infrastructure costs and limited availability of labeled data for failures. While most manufacturing AI applications focus...
Background: Although electronic health records (EHR) provide useful insights into disease patterns and patient treatment optimisation, their reliance on unstructured data presents a difficulty. Echocardiography reports, which provide extensive pathol...
Risk management of electric power transmission lines requires knowledge from different areas such as the environment, land, investors, regulations, and engineering. Despite the widespread availability of databases for most of those areas, integrating...
Due to the insufficient number and uneven distribution of urban rainfall stations, research on urban flooding disasters is limited. With the development of big data research, many scholars have applied big data to natural disaster research. In this p...
The identification of human behavior can provide useful information across multiple job spectra. Recent advances in applying data-based approaches to social sciences have increased the feasibility of modeling human behavior. In particular, studying h...
Cost is a key performance indicator for evaluating the success of architectural construction projects. While previous studies have relied on quantitative data and statistical models to evaluate cost performance, recent advancements in methods have en...
Patients within the US Department of Veterans Affairs (VA) healthcare system have the option of receiving care at facilities external to the VA network. This work presents a method for identifying external hospitalizations among the VA’s patien...
The most common pattern types for anode structuring, in particular the line, grid, and hexagonal-arranged hole pattern were evaluated in a comparable setup in full-cells and symmetrical cells. The cells with structured electrodes were compared to ref...
In this paper, we propose a quantitative evaluation method for navigation safety in coastal waters based on unstructured grids. Initially, a comprehensive analysis was conducted on various factors affecting navigation safety, including natural condit...
Business and science are using sentiment analysis to extract and assess subjective information from the web, social media, and other sources using NLP, computational linguistics, text analysis, image processing, audio processing, and video processing...
This paper documents the condition-based maintenance (CBM) of power transformers, the analysis of which relies on two basic data groups: structured (e.g., numeric and categorical) and unstructured (e.g., natural language text narratives) which accoun...
Data modeling and dimensionality reduction are important research points in the field of big data. At present, there is no effective model to realize the consistent representation and fusion of different types of data of students in unstructured camp...
Networked Microgrids (NMGs) have revolutionized the energy landscape by enhancing grid flexibility and decentralizing power generation, playing a pivotal role in the development of smart cities. Distributed Energy Resources (DERs) are a fundamental c...
Currently, most of the transportation systems require changes to intelligent transportation systems, but most of them focus on efficient transportation rather than on improvement in human life. Sometimes, traffic systems are designed for economic val...
The Internet is increasingly a source of data for geographic information systems, as more data becomes linked, available through application programing interfaces (APIs), and more tools become available for handling unstructured web data. While many...
In cartography, generalization is a key process used to simplify complex geographic information, making it suitable for display at different scales while maintaining its essential meaning. When representing high-density road networks on a fixed scree...
Organizations have been challenged by the need to process an increasing amount of data, both structured and unstructured, retrieved from heterogeneous sources. Criminal investigation police are among these organizations, as they have to manually proc...
Pneumonia and pulmonary thromboembolism (PTE) are both respiratory diseases; their diagnosis is difficult due to their similarity in symptoms, medical subjectivity, and the large amount of information from different sources necessary for a correct di...
The autonomous navigation of unmanned ground vehicles (UGVs) in unstructured environments, such as agricultural or forestry settings, has been the subject of extensive research by various investigators. The navigation capability of a UGV in unstructu...
Autonomous driving in unstructured environments faces challenges such as missing road boundaries, terrain variations, random obstacle distributions, and complex vehicle–terrain interactions, making it difficult to achieve safe navigation by rel...
The most crucial component of any smart city traffic management system is traffic flow prediction. It can assist a driver in selecting the most efficient route to their destination. The digitalization of closed-circuit television (CCTV) systems has r...
This paper presents a scalable machine learning pipeline for extracting actionable, product-related insights from user-generated social media comments. Leveraging sentence embeddings from SBERT and unsupervised clustering (k-Means and agglomerative),...
This paper presents a modeling study conducted on the central Oregon coast for wave resource characterization, using the unstructured grid Simulating WAve Nearshore (SWAN) model coupled with a nested grid WAVEWATCH III® (WWIII) model. The flexibility...
The work presented in this paper is motivated by the acknowledgement that a complete and updated systematic literature review (SLR) that consolidates all the research efforts for Big Data modeling and management is missing. This study answers three r...
Nowadays, financial institutions increasingly leverage artificial intelligence to enhance decision-making and optimize investment strategies. A specific application is the automatic analysis of large volumes of unstructured textual data to extract re...
With the increasing digitalization of maritime transportation, the demand for structured and interoperable data has grown. While the S-100 framework developed by the International Hydrographic Organization (IHO) provides a foundation for standardizin...
In live-streaming e-commerce systems, massive volumes of user-generated danmaku constitute a critical yet underutilized source of business intelligence. However, transforming such unstructured, noisy, and highly context-dependent textual data into st...
9 October 2021
Extracting clinical concepts, such as problems, diagnosis, and treatment, from unstructured clinical narrative documents enables data-driven approaches such as machine and deep learning to support advanced applications such as clinical decision-suppo...
The present study describes the development of a wearable device designed to assist those who work in an unstructured posture. In the manufacturing sector, industrial accidents have been steadily on the rise due to poor work environments and excessiv...
In the age of digitalization, the collection and analysis of large amounts of data is becoming increasingly important for enterprises to improve their businesses and processes, such as the introduction of new services or the realization of resource-e...
Ensuring high data quality in traffic crash datasets is critical for effective safety analysis and policymaking. This study presents an AI-assisted framework for auditing crash data integrity by detecting potentially mislabeled records related to con...
In recent years, transportation system safety analysis has become increasingly challenging and highly demanding. Unstructured data contain sufficient information from which inherent interactions can be extracted. Determining how to process and fuse a...
Unstructured free play among children has declined, while digital play via screens has increased, raising developmental concerns. A recent synthesis of this shift is lacking. To review studies (2020–2025) on the decline of unstructured play and...
Modern organizations are challenged to enact a digital transformation and improve their competitiveness while contributing to the ninth Sustainable Development Goal (SGD), “Build resilient infrastructure, promote sustainable industrialization a...
We examined eligibility criteria from recent oncology clinical trials to see whether real-world data (RWD) from electronic health records (EHRs) could be used to create external control groups for clinical trials. Trials were identified from the Aggr...
Objectives: This article focuses on describing the main characteristics of the application of NLP in the qualitative assessment of quality of life, as well as its implications and challenges. Methods: The qualitative methodology allows analysing pati...
With the popularization of social networks, the abundance of unstructured data regarding environmental complaints is rapidly increasing. This study established a text mining framework for Chinese civil environmental complaints and analyzed the charac...
Background/Objectives: Childhood cancer survivors face long-term cancer-related health risks, and daily behaviours, such as physical activity and recreational screen use, may influence their long-term overall wellbeing. Yet, little is known about sur...
Sentiment analysis is a crucial component of text mining and natural language processing (NLP), involving the evaluation and classification of text data based on its emotional tone, typically categorized as positive, negative, or neutral. While signi...
The detection of corruption-related indicators within unstructured, textual procurement data remains a complex task due to linguistic ambiguity, contextual variation and domain-specific terminology. This study presents a comparative evaluation of thr...
Particularly in the last decade, Internet usage has been growing rapidly. However, as the Internet becomes a part of the day to day activities, cybercrime is also on the rise. Cybercrime will cost nearly $6 trillion per annum by 2021 as per the cyber...
Mining supply chains are strategically important yet difficult to observe because firm-to-firm relationships are fragmented across unstructured public disclosures. This paper applies a retrieval-augmented large language model (LLM) framework to recon...
Frequent accidents in the construction sector arise from the dynamic coupling of multiple risk factors, while conventional single-factor approaches fail to capture the underlying complexity. Drawing on 702 accident investigation reports, this study d...
Analyzing accident reports to absorb past experiences is crucial for construction site safety. Current methods of processing textual accident reports are time-consuming and labor-intensive. This research applied the LDA topic model to analyze constru...
Recurrence is a critical aspect of breast cancer (BC) that is inexorably tied to mortality. Reuse of healthcare data through Machine Learning (ML) algorithms offers great opportunities to improve the stratification of patients at risk of cancer recur...
With the recent growth of the Internet, the volume of data has also increased. In particular, the increase in the amount of unstructured data makes it difficult to manage data. Classification is also needed in order to be able to use the data for var...
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