We present a semi-automatic framework for transcribing foreign personal names into Lithuanian, aimed at reducing pronunciation errors in text-to-speech systems. Focusing on noisy, web-crawled data, the pipeline combines rule-based filtering, morpholo...
Public participation is crucial in the process of urban governance in smart-city initiatives to enable urban planners and policy makers to take account of the real public needs. Our study aims to develop an analytical framework using citizen-centred...
This paper has tried to execute accurate demand forecasting by utilizing big data visualization and proposes a flexible and balanced electric power production big data virtualization based on a photovoltaic power plant. First of all, this paper has t...
This article presents a study on the multi-class classification of job postings using machine learning algorithms. With the growth of online job platforms, there has been an influx of labor market data. Machine learning, particularly NLP, is increasi...
Ethnopharmacology experts face several challenges when identifying and retrieving documents and resources related to their scientific focus. The volume of sources that need to be monitored, the variety of formats utilized, and the different quality o...
This method article presents the nuts and bolts of an AI-enabled approach to extracting and analyzing social media data. The method is based on our previous rapidly cited COVID-19 research publication, working on a dataset of more than 14,000 news ar...
To build state-of-the-art Neural Machine Translation (NMT) systems, high-quality parallel sentences are needed. Typically, large amounts of data are scraped from multilingual web sites and aligned into datasets for training. Many tools exist for auto...
Background/Objectives: The rapidly evolving crisis of Novel Synthetic Opioids (NSOs) poses a serious and growing threat for global public health. NSOs include prescription/non-prescription opioids (fentanyl, non-fentanyl analogues), herbal derivative...
Object detection and recognition are crucial in the field of computer vision and are an active area of research. However, in actual object recognition processes, recognition accuracy is often degraded due to resolution mismatches between training and...
With the rapid pace of urbanization, enhancing the quality of life has become an urgent demand for the general public in both developed and developing countries. This study addresses the pressing need to understand the spatial distribution and underl...
Cultural ecosystem services (CES) provided by 12 major urban parks on the Macau Peninsula were quantitatively evaluated using social media data. Furthermore, the potential implications of these findings for cultural heritage preservation and landscap...
Movie and TV subtitles are frequently employed in natural language processing (NLP) applications, but there are limited Japanese-Chinese bilingual corpora accessible as a dataset to train neural machine translation (NMT) models. In our previous study...
The World Health Organization (WHO) declared the COVID-19 pandemic on 11 March 2020. As COVID-19 has spread, lockdowns have been declared all over the world, including the United States, Europe, Asia, Africa, and South Korea. Consequently, it has cha...
The housing market in Chinese metropolises have become inflated significantly over the last decade. In addition to an economic upturn and housing policies that have potentially fueled the real estate bubble, factors that have contributed to the spati...
Deep neural networks (DNNs), due to their over-parameterization and memorization capacity, are prone to fitting incorrect labels in training data, which can substantially degrade their performance. Consequently, LNL has attracted increasing attention...
This study addresses the limitations of traditional job recommendation systems that rely on static datasets, making them less responsive to dynamic job market changes. While existing job platforms address job search with an untransparent logic follow...
Arabic natural language processing (NLP) faces major difficulties due to the language’s rich morphological structure and the scarcity of high-quality datasets, especially for educational material distributed across diverse online platforms. Man...
In recent years, transformer-based models have played a significant role in advancing language modeling for natural language processing. However, they require substantial amounts of data and there is a shortage of high-quality non-English corpora. So...
Currently, there are only a limited number of Japanese-Chinese bilingual corpora of a sufficient amount that can be used as training data for neural machine translation (NMT). In particular, there are few corpora that include spoken language such as...
As an essential basic function of grassland resource surveys, grassland-type recognition is of great importance in both theoretical research and practical applications. For a long time, grassland-type recognition has mainly relied on two methods: man...
Social networking and network socialization provide abundant text information and social relationships into our daily lives. Making full use of these data in the big data era is of great significance for us to better understand the changing world and...
Temporal intent is an important component of events. It plays an important role in collecting them from the web with focused crawlers. However, traditionally focused crawlers usually only consider factors such as topic keywords, web page content, and...
With the advance of the World-Wide Web (WWW) technology, people can easily share content on the Web, including geospatial data and web services. Thus, the “big geospatial data management” issues start attracting attention. Among the big geospatial da...
As digitalization is gradually transforming reality into Big Data, Web search engines and recommender systems are fundamental user experience interfaces to make the generated Big Data within the Web as visible or invisible information to Web users. I...
This paper presents the processing steps needed in order to have a fully functional vertical search engine. Four actions are identified (i.e., retrieval, extraction, presentation, and delivery) and are required to crawl websites, get the product info...
Dark web forums are critical platforms for illicit activities and anonymous communication, making their analysis essential for cybersecurity, law enforcement, and academic research. This systematic literature review synthesises methodologies for data...
Understanding the past, present, and changing behavior of the climate requires close collaboration of a large number of researchers from many scientific domains. At present, the necessary interdisciplinary collaboration is greatly limited by the diff...
Automatic discovery of isolated land cover web map services (LCWMSs) can potentially help in sharing land cover data. Currently, various search engine-based and crawler-based approaches have been developed for finding services dispersed throughout th...
Trust is a critical element when it comes to news articles, and an important problem is how to ensure trust in the published information on news websites. First, this paper describes the inner workings of a proposed news-retrieval and aggregation arc...
The feedback shared by consumers on e-commerce platforms holds immense value in marketing, as it offers insights into their opinions and preferences, which are readily accessible. However, analyzing a large volume of reviews manually is impractical....
In this paper, we propose a fully automated system to extend knowledge graphs using external information from web-scale corpora. The designed system leverages a deep-learning-based technology for relation extraction that can be trained by a distantly...
The widespread adoption of web applications has led to a significant increase in the number of automated cyberattacks. Parameter tampering attacks pose a substantial security threat, enabling privilege escalation and unauthorized data exfiltration. T...
This study examines the structural, semantic, and temporal evolution of strategy- and competition-oriented web scraping research, focusing on the legal and governance boundaries of data-driven competitive advantage. A purposively delimited corpus of...
This article presents an approach for spellchecking and autocorrection using web data for morphologically complex languages (in the case of Kazakh language), which can be considered an end-to-end approach that does not require any manually annotated...
Lender trust is important to ensure the sustainability of P2P lending. This paper uses web crawling to collect more than 240,000 unique pieces of comment text data. Based on the mapping relationship between emotion and trust, we use the lexicon-based...
Robotic agents are spreading, incarnated as embodied entities, exploring the tangible world and interacting with us, or as virtual agents crawling over the web, parsing and generating data. In both cases, they require: (i) processes to acquire inform...
With the rapid advancement in Generative Artificial Intelligence (GenAI), AI-generated content (AIGC) lacking human cognitive oversight is increasingly permeating open web environments and academic communication systems. This study integrates longitu...
This paper presents a deep-learning-based classification model that aims to detect diverse pest infections in strawberry plants. The proposed model enables the timely identification of pest symptoms, allowing for prompt and effective pest management...
The first professional night-time light remote sensing satellite in China, Luojia1-01, has raised the resolution of night-time light data to 130 m, which provides a possibility for the study of small-scale night-time light. This paper is the first re...
The purpose of this study is to make good use of the massive amount of online user comment data to explore and analyze the dimensions of customer-perceived value and the importance of each dimension, given the background of China’s huge e-comme...
Recent advancements in AI research, particularly in spatial layout generation, highlight its capacity to enhance human creativity by swiftly providing architects with numerous alternatives during the pre-design phase. The complexity of architectural...
Since the outbreak of COVID-19, in addition to the continuous increment in the number of infected patients, the number of COVID-19-related papers has also increased significantly. According to the statistics, its number even exceeds the research of s...
Fire safety on construction sites has been rarely studied because fire accidents have a lower occurrence compared to construction’s “Fatal Four”. Despite the lower occurrence, construction fire accidents tend to have a larger severity of impact. This...
Post-occupancy evaluation is a critical mechanism for ensuring the sustained success and continuous improvement of industrial heritage revitalization initiatives. The quality of the visitor experience plays a key role in determining a project’s...
The quality of travel for residents has improved in China’s urban renewal development, but there are still barriers to the activities of disadvantaged groups like people with disabilities in the city, including challenges with accessible travel...
The construction industry has high accident and fatality rates owing to time and cost pressures as well as hazardous working environments caused by heavy construction equipment and temporary structures. Thus, safety management at construction sites i...
This study utilized web crawling and text analysis to collect weekly data from July 2018 to March 2022. Using the spiral of silence theoretical framework, it explores the relationship between consumer online attention during sudden animal epidemics a...
Traditional methods for assessing urban waterlogging hazards lack real-time efficiency. This study develops a rapid hazard assessment method for urban waterlogging events using social media data and large language models, with the urban waterlogging...
The purpose of this study was to predict the online sales volume for organic products, identify important factors for selling organic products, and suggest web marketing strategies for organic product sales. Through the review of organic products on...
Due to the availability of a vast amount of unstructured data in various forms (e.g., the web, social networks, etc.), the clustering of text documents has become increasingly important. Traditional clustering algorithms have not been able to solve t...
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