Research on the Construction and Application of Problem-Method-Oriented Academic Graph Empowered by LLM

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 16, 2025

Nowadays, the volume of literature in each field is huge and growing rapidly, which posts challenge to researchers’ review. In this circumstance, developing useful tool for achieving efficient management high value. Traditional tools, such as tools key word searching, paper recommendation, relation visualization, keyword cloud drawing, are not suitable conducting content-level To address issues traditional a novel problem method-oriented fine-grained academic graph proposed facilitate exploration research questions, methodologies, study perspectives, their connections hidden massive literature. For building graph, new ontology dedicated describing features developed, an innovative multi-relation join extraction model proposed, creative approach leveraging Large Language Models (LLM) augment triplet results generated by supervised-learning developed. Experiments on widely used benchmark datasets show that able achieve at least 8.01% 8.65% improvement entity identification classification respectively, compared with state-of-the-art models. The visualized demonstration shows our capable accurately capturing network, method network hot topics Q&A system supported demonstrates really helpful data code work available https://github.com/asilcr/AcademicGraph.

Язык: Английский

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ИИ как драйвер экономики Тайваня

Modern Economy Success, Год журнала: 2025, Номер 1, С. 42 - 49

Опубликована: Янв. 9, 2025

целью данной статьи является оценка влияния развития технологий искусственного интеллекта на экономическое развитие Тайваня. В качестве объекта исследования выступает экономика Предметом влияние Методы: в методов статье применены качественные и количественные методы. Среди примененных количественных можно отметить метод статистического анализа, сравнительного анализа. качественных – сравнения, прогнозирования, обзор литературы. Результаты (Findings): рассмотрено экономику Отмечена связь между «бумом ИИ» положительной динамикой экономических показателей Автор приходит к выводу, что Тайваня получает больший рост от производства экспорта высокотехнологичных компонентов, используемых для ИИ, чем внедрения производственные процессы. Помимо позитивного отмечены вызовы, с которыми может столкнуться Тайвань, а также предложены возможные решения. Выводы: искусственный интеллект стал драйвером экономического роста последние несколько лет, укрепив его позиции глобальной цепочке поставок высоких технологий. Несмотря значительный вклад ИИ экономику, существует ряд вызовов, включая растущую зависимость полупроводниковой отрасли, сопротивление развитых стран зависимости Тайваня, усиление социального неравенства, энергетическую нагрузку демографические риски. Для обеспечения устойчивого необходимо более активное внедрение диверсификация экономики решение обозначенных долгосрочных проблем. Тогда сможет стать долгосрочной основе не создавать угроз экономике острова. : the purpose of this article is to assess impact artificial intelligence technologies on Taiwan's economic development. The object study economy Taiwan. subject Methods: qualitative and quantitative methods are used as research in article. Among used, statistical analysis method comparative can be noted. comparison method, forecasting literature review. Findings: considered. A connection noted between "AI boom" positive dynamics indicators. author concludes that receives greater growth from production export high-tech components develop AI than introduction into processes. In addition impact, paper also notes challenges Taiwan may face suggests possible solutions. Conclusions: Artificial has become a driver recent years, strengthening its position global supply chain products. Despite significant contribution economy, there number challenges, including growing dependence semiconductor industry, resistance developed countries Taiwan, increasing social inequality, energy burden, demographic risks. To ensure sustainable growth, it necessary more actively implement AI, diversify solve identified long-term problems. Then basis not pose threat island's economy.

Язык: Русский

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Artificial intelligence in education and EFL teachers’ attitudes: scale development and validation

Innovation in Language Learning and Teaching, Год журнала: 2025, Номер unknown, С. 1 - 17

Опубликована: Апрель 24, 2025

Язык: Английский

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From AI to the Era of Explainable AI in Healthcare 5.0: Current State and Future Outlook

Expert Systems, Год журнала: 2025, Номер 42(6)

Опубликована: Апрель 29, 2025

ABSTRACT Artificial intelligence (AI) and explainable artificial (XAI) are advancing rapidly, with the potential to deliver significant benefits modern society. The healthcare sector, in particular, has experienced transformative changes; overall, these technologies helping address numerous challenges, such as cancer cell detection, tumour zone identification animal bodies, predictions of major minor diseases, diagnosis, more. This article provides an in‐depth detailed overview AI XAI, focusing on recent trends their implications for Healthcare 5.0 applications. Initially, study examines key concepts exceptional features AI, 5.0. Additional emphasis is placed state‐of‐the‐art practices currently being implemented healthcare, particularly those involving XAI. Subsequently, it establishes a coherent link between XAI 5.0, grounded contemporary advancements. Based findings, algorithms recommended initial obstacles integrating into framework. Proposals further enhancing performance through integration its unique discussed detail. work also implementation strategies highlights model‐specific within frameworks Particular attention given model settings, emphasising contributions improved patient feedback delivery more sophisticated care. Most importantly, this research support sustainable advancements Finally, issues analysed, open discussion presented future guidelines blending

Язык: Английский

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Enhancing risk management in hospitals: leveraging artificial intelligence for improved outcomes

Italian Journal of Medicine, Год журнала: 2024, Номер 18(2)

Опубликована: Апрель 15, 2024

In hospital settings, effective risk management is critical to ensuring patient safety, regulatory compliance, and operational effectiveness. Conventional approaches assessment mitigation frequently rely on manual procedures retroactive analysis, which might not be sufficient recognize respond new risks as they arise. This study examines how artificial intelligence (AI) technologies can improve in healthcare facilities, fortifying safety precautions guidelines while improving the standard of care overall. Hospitals proactively identify mitigate risks, optimize resource allocation, clinical outcomes by utilizing AI-driven predictive analytics, natural language processing, machine learning algorithms. The different applications AI are discussed this paper, along with opportunities, problems, suggestions for their use settings.

Язык: Английский

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Artificial Intelligence in Retail Marketing: Research Agenda Based on Bibliometric Reflection and Content Analysis (2000–2023)

Informatics, Год журнала: 2024, Номер 11(4), С. 74 - 74

Опубликована: Окт. 9, 2024

Artificial intelligence (AI) is fundamentally transforming the marketing landscape, enabling significant progress in customer engagement, personalization, and operational efficiency. The retail sector has been at forefront of AI revolution, adopting technologies extensively to transform consumer interactions, supply chain management, business performance. Given its early adoption AI, industry serves as an essential case context for investigating broader implications behavior. Drawing on 404 articles published between 2000 2023, this study presents a comprehensive bibliometric content analysis applications marketing. used VOSviewer (1.6.20.0 version) Bibliometrix (version 4.3.1) identify important contributors, top institutions, key publication sources. Co-occurrence keyword co-citation analyses were map intellectual networks highlight emerging themes. Additionally, focused 50 recent was selected based their relevance, timeliness, citation influence. It revealed six primary research streams: (1) behavior, (2) marketing, (3) performance, (4) sustainability, (5) (6) trust. These streams categorized through thematic relevance theoretical significance, emphasizing AI’s impact sector. contributions are twofold. Theoretically, it integrates existing outlines future areas such role domain From empirical standpoint, highlights how can be applied enhance experiences improve operations.

Язык: Английский

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Innovation management among the Indian small and medium-sized enterprises focusing on artificial intelligence: Opportunities and the way forward

Indian Journal of Commerce & Management Studies, Год журнала: 2024, Номер XV(2), С. 10 - 17

Опубликована: Май 23, 2024

Introduction:The current study details about how artificial intelligence (AI) is applied in innovation management among Indian small and medium-sized enterprises (SMEs).It a first-of-its-kind that delves into this research domain SMEs whereas the provides in-depth insights topic undertaken.Methodology: This narrative review considers publications, company reports, government books, materials published by institutions, other web pages to analyze existing information achieve objectives.Findings: The has identified challenges involved AI implementation both during its adoption continued use organizations terms of human resources, ethics, technology, organizational, economic aspects.It also found limitations faced elsewhere, while discusses opportunities overcome issues SMEs.Implications: policymakers, governments, educational academia, skill development centers are provided with various suggestions from outcomes if implemented, can uplift contributions made toward their gross domestic product.Originality: article dealt impact on aspect SMEs.

Язык: Английский

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Artificial Intelligence and Machine Learning in Neuroregeneration: A Systematic Review

Cureus, Год журнала: 2024, Номер unknown

Опубликована: Май 30, 2024

Artificial intelligence (AI) and machine learning (ML) show promise in various medical domains, including imaging, precise diagnoses, pharmaceutical research. In neuroscience neurosurgery, AI/ML advancements enhance brain-computer interfaces, neuroprosthetics, surgical planning. They are poised to revolutionize neuroregeneration by unraveling the nervous system's complexities. However, research on is fragmented, necessitating a comprehensive review. Adhering Preferred Reporting Items for Systematic Reviews Meta-Analyses (PRISMA) recommendations, 19 English-language papers focusing were selected from total of 247. Two researchers independently conducted data extraction quality assessment using Mixed Methods Appraisal Tool (MMAT) 2018. Eight studies deemed high quality, 10 moderate, four low. Primary goals included diagnosing neurological disorders (35%), robotic rehabilitation (18%), drug discovery (12% each). ranged analyzing imaging (24%) animal models electronic health records (12%). Deep accounted 41% techniques, while standard ML algorithms constituted 29%. The review underscores growing interest neuroregenerative medicine, with increasing publications. These technologies aid diseases facilitating functional recovery through robotics targeted stimulation. AI-driven holds identifying therapies. Nonetheless, addressing existing limitations remains crucial this rapidly evolving field.

Язык: Английский

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Digitizing Development: Enablers and Inhibitors of Mobile App-Based Population Census Adoption

Signals and communication technology, Год журнала: 2024, Номер unknown, С. 71 - 93

Опубликована: Янв. 1, 2024

Язык: Английский

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Avances en el uso de inteligencia artificial para la mejora del control y la detección de fraudes en organizaciones

Revista Cientifica de Sistemas e Informatica, Год журнала: 2024, Номер 4(2), С. e671 - e671

Опубликована: Июль 10, 2024

El estudio analizó el uso de Inteligencia Artificial (IA) para la mejora del control y detección fraudes en organizaciones, abarcando una revisión sistemática 59 artículos científicos publicados entre 2020 2023. Las tecnologías predominantes identificadas incluyen machine learning, deep learning blockchain, que han mostrado un impacto precisión eficiencia manejo grandes volúmenes datos. Se observó estas no solo optimizan los controles internos las sino también refuerzan seguridad transparencia transacciones, principalmente sectores financiero empresarial. Los resultados análisis sugieren adopción emergentes permite reducir falsos positivos mejorar tiempo real fraudes, gracias a algoritmos optimización utilizados estudios. Sin embargo, destacó desafíos, como interoperabilidad sistemas existentes capacitación personal manejar herramientas avanzadas. En conclusión, implementación IA asociadas es tendencia crecimiento proporciona soluciones avanzadas enfrentar amenazas actuales, aunque necesario seguir abordando desafíos maximizar su efectividad largo plazo.

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