Iskanje po katalogu digitalne knjižnice

Opis: This paper investigates emerging technological trends in web commerce and examines user perceptions through a pilot survey. Key innovations include IoT, AI, ML, chatbots, social and voice commerce, as well as immersive technologies like AR and VR. These tools enhance personalization, automate services, and support better consumer decision-making. The pilot study, based on an online questionnaire, explores user behaviour, expectations, and attitudes toward these developments. Results show that while users are familiar with technologies like chatbots and personalization, awareness of AR and VR remains low. Concerns about security and data privacy significantly influence user trust. The findings highlight the need for seamless technological integration, increased user education, and transparent communication to build trust and improve the digital shopping experience.
Ključne besede: web commerce, e-commerce trends, internet of things (IoT), artificial intelligence (AI), machine learning (ML), chatbots, augmented reality (AR), virtual reality (VR), voice commerce, user perception, digital transformation, data privacy
Objavljeno v DKUM: 29.08.2025; Ogledov: 0; Prenosov: 3
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Opis: The article explores the potential of PDFGear Copilot, a chatbot-based PDF editing tool, in assisting with the analysis of historical documents. We evaluated the chatbot's performance on a document relating to the Slovenian War of Independence. We included 25 factual and 5 interpretative questions to address its formal characteristics and content details, assess its capacity for in-depth interpretation and contextualized critical analysis, and evaluate the chatbot’s language use and robustness. The chatbot exhibited some ability to answer factual questions, even though its performance varied. It demonstrated proficiency in navigating document structure, named entity recognition, and extracting basic document information. However, performance declined significantly in tasks such as document type identification, content details, and tasks requiring deeper text analysis. For interpretative questions, the chatbot's performance was notably inadequate, failing to link cause-and-effect relationships and provide the depth and nuance required for historical inquiries.
Ključne besede: chatbots, historical document analyses, Yugoslavia, wars, generative, artificial intelligence, large language models
Objavljeno v DKUM: 18.07.2025; Ogledov: 0; Prenosov: 7
Celotno besedilo (1,20 MB)
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Opis: This paper reviews benchmarking methods for evaluating large language models (LLMs) in healthcare settings. It highlights the importance of rigorous benchmarking to ensure LLMs' safety, accuracy, and effectiveness in clinical applications. The review also discusses the challenges of developing standardized benchmarks and metrics tailored to healthcare-specific tasks such as medical text generation, disease diagnosis, and patient management. Ethical considerations, including privacy, data security, and bias, are also addressed, underscoring the need for multidisciplinary collaboration to establish robust benchmarking frameworks that facilitate LLMs' reliable and ethical use in healthcare. Evaluation of LLMs remains challenging due to the lack of standardized healthcare-specific benchmarks and comprehensive datasets. Key concerns include patient safety, data privacy, model bias, and better explainability, all of which impact the overall trustworthiness of LLMs in clinical settings.
Ključne besede: artificial intelligence, benchmarking, chatbots, healthcare, large language models, natural language processing
Objavljeno v DKUM: 12.05.2025; Ogledov: 0; Prenosov: 3
Celotno besedilo (943,83 KB)
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