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检索条件"任意字段=Conference on Visual Data Exploration and Analysis V"

共 5114 条记录，以下是11-20 订阅

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An Integrated System for Interacting with Multi-Page Scholarly Documents 21

An Integrated System for Interacting with Multi-Page Scholar...

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21st conference on Information and Research Science Connecting to Digital and Library Science, IRCDL 2025

作者： Massai, Lorenzo Marinai, Simone DINFO - University of Florence via S. Marta 3 Firenze Italy

In this work we present a preliminary version of a comprehensive interface for supporting users to interact with scholarly documents, enabling multi-layered exploration and offering deeper insights by integrating diverse features and contextual information. By bridging diverse information our work pursues the identification, characterization, and linking of visual elements to semantic and context data, leveraging large language models for interoperability. Recent advances in retrieval augmented generation are also exploited to address some language models limitations, allowing them to access latent information from document representations such as graph and vector embeddings. The system under development performs an analysis of input documents and enables the extraction of visual and semantic features, making them accessible in a comprehensive framework. The association of structural information to visual data allows formal analysis of documents and is exploited in our model to enhance visual extraction, performing a novel ontology-based constraint violation detection. The information extracted through this framework is semantically explorable, providing access to the document structure, which can be exploited in many applications like question answering and document understanding. © 2025 Copyright for this paper by its authors.

关键词： Latent semantic analysis

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10th International Workshop on Big data Management and Service, BDMS 2024, 9th International Workshop on Big data Quality Management, BDQM 2024, DASFAA 2024 Workshop on Emerging Results in data Science and Engineering, ERDSE 2024 and 8th International Workshop on Graph data Management and analysis, GDMA 2024 held in conjunction with 29th International conference on database Systems for Advanced Applications, DASFAA 2024

10th International Workshop on Big Data Management and Servi...

引用

10th International Workshop on Big data Management and Service, BDMS 2024, 9th International Workshop on Big data Quality Management, BDQM 2024, DASFAA 2024 Workshop on Emerging Results in data Science and Engineering, ERDSE 2024 and 8th International Workshop on Graph data Management and analysis, GDMA 2024 held in conjunction with 29th International conference on database Systems for Advanced Applications, DASFAA 2024

ISBN: (纸本)9789819609130

The proceedings contain 26 papers. The special focus in this conference is on Big data Management and Service. The topics include: FAITH: A Fast, Accurate, and Lightweight database-Agnostic Learned Cost Model;fast Approximate Temporal Butterfly Counting on Bipartite Graphs via Edge Sampling;Financial-ICS: Identifying Peer Firms via LongBERT from 10K Reports;establishing a Decentralized Diamond Quality Management System: Advancing Towards Global Standardization;co-estimation of data Types and Their Positional Distribution;Enhancing Load Forecasting with vAE-GAN-Based data Cleaning for Electric vehicle Charging Loads;audio-Guided visual Knowledge Representation;boundary Point Detection Combining Gravity and Outlier Detection Methods;A Meta-learning Approach for Category-Aware Sequential Recommendation on POIs;automatic Post-editing of Speech Recognition System Output Using Large Language Models;comparative analysis with Multiple Large-Scale Language Models for Automatic Generation of Funny Dialogues;effectiveness of the Programmed visual Contents Comparison Method for Two Phase Collaborative Learning in Computer Programming Education: A Case Study;generating Achievement Relationship Graph Between Actions for Alternative Solution Recommendation;generating News Headline Containing Specific Person Name;Investigating Evidence in Sentence Similarity Using MASK in BERT;acceleration of Synopsis Construction for Bounded Approximate Query Processing;Query Expansion in Food Review Search with Synonymous Phrase Generation by LLM;Question Answer Summary Generation from Unstructured Texts by Using LLMs;Real Estate Information exploration in vR with LoD Control by Physical Distance;voices of Asynchronous Learning Students: Revealing Learning Characteristics Through vocabulary analysis of Notes Tagged in videos;review Search Interface Based on Search Result Summarization Using Large Language Model;yes-No Flowchart Generation for Interactive exploration of Personalized Health Improve

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A comprehensive exploration of strain-induced crystallization through surface calorimetry and thermodynamics analysis 13th

A comprehensive exploration of strain-induced crystallizatio...

引用

13th European conference on Constitutive Models for Rubber

作者： Khiem, v. N. Le Cam, J. -B. Univ Rennes CNRS UMR 6251 Inst Phys Rennes France

ISBN: (纸本)9781032851648;9781003516880;9781032851389

To date, investigations of strain-induced crystallization are out of reach for most mechanical laboratories due to costly X-ray diffraction facilities. Making use of the exothermic nature of such phase transition, infrared thermography based quantitative surface calorimetry has provided an alternative approach to investigate strain-induced crystallinity in conventional mechanical laboratories. Moreover, this calorimetric approach provides continuum quantities of interest for enriching and validating constitutive models. Nevertheless, its application has been confined to the evaluation of crystallinity under only the loading case. In this contribution, strain-induced crystallization is investigated in various types of natural rubbers by coupling data analysis with domain knowledge of thermodynamics. It pushes the boundaries of the current quantitative surface calorimetry methodology to explore not only the crystallinity during loading-unloading cycles but also different compositions of the internal energy.

关键词： Calorimeters

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AI-Driven Personalized Skincare Recommendations 3

AI-Driven Personalized Skincare Recommendations

引用

3rd International conference on Electronics and Renewable Systems, ICEARS 2025

作者： Perumal, Iyyanar Kalaivani, P. Naveenkumar, A. Saran, v. Sriram, K. Suruthi, N. Sona College of Technology Department of Information Technology Salem India Kongu Engineering College Department of Cse Perundurai India

ISBN: (纸本)9798331509675

This study investigates the utilization of artificial intelligence (AI) to transform skincare product recommendations and the formulation of individualized routines through the analysis of user inputs and characteristics. The system utilizes data including skin type, acne count, oiliness level, and Uv exposure, using KNearest Neighbors (KNN) for personalized product suggestions. Natural Language Processing (NLP) approaches are utilized to develop tailored 7-day skincare regimen recommendations by examining product and user problems, converting unstructured data into actionable insights. Moreover, deep learning algorithms are employed for real-time image-based assessments of skin conditions, facilitating precise acne diagnosis and oiliness evaluation. The system integrates visual data with textual analysis, continually adapting through user feedback to improve accuracy and relevance. This article highlights the capacity of AI-driven methods to automate routine generation and provide tailored product recommendations, fostering innovation in the cosmetics sector through a thorough, data-oriented strategy. © 2025 IEEE.

关键词： k-nearest neighbors

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DM-vis: A Graph-Based data Reconnaissance System for Multi-domain Urban data 41st

DM-Vis: A Graph-Based Data Reconnaissance System for Multi...

引用

41st Computer Graphics International conference, CGI 2024

作者： Wang, Hesong Wang, Song Wang, Yanru Long, Hao School of Computer Science and Technology Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9783031818059

As urbanization accelerates, data on the diverse aspects of urban life, including the environment, finance, and transportation, are increasing exponentially. Single-domain data analysis falls short for complex tasks, necessitating multi-source data integration to offer decision-makers a holistic view of interconnections and trends. However, challenges arise in effectively representing data associations and swiftly identifying relevant datasets. This paper proposes techniques to integrate multi-domain urban data relationships and facilitate the acquisition of target datasets. We introduce a method to transform data entities into association graphs and a data extraction method to aid users in understanding data relationships and acquiring target datasets. Using these methods, we developed DM-vis, a data reconnaissance visual analysis system, to facilitate data integration and exploration from multiple sources. Real-data case studies and positive feedback from users and experts validate the utility and reliability of our approach. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： data extract data integration data reconnaissance multi-domain data query embedding

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Czech Salivary Gland database

Czech Salivary Gland Database

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18th International Joint conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2025

作者： Jelínek, vojtĕch Brůha, Petr Kalfĕrt, David Nový, Pavel Department of Computer Science and Engineering Faculty of Applied Sciences University of West Bohemia Univerzitní 8 Pilsen Czech Republic Department of Otorhinolaryngology and Head and Neck Surgery 1st Faculty of Medicine University Hospital Motol Charles University V Uvalu 84 Prague150 06 Czech Republic

Salivary gland tumors require comprehensive data collection and analysis to support clinical decision-making, yet existing databases need more focus on specific tumor-related data and visualization tools. This absence hinders oncologists’ ability to track patient outcomes effectively and identify potential prognostic indicators. To address this, we developed the Czech Salivary Gland database (CSGDB), a specialized clinical application designed to manage patient data and provide visual analytics. The database includes secure and anonymized data handling alongside Kaplan-Meier survival analysis for outcome visualization. Deployed at the University Hospital in Motol, CSGDB empowers healthcare professionals with enhanced tools for tracking and analyzing patient progress, ultimately contributing valuable data and insights to the field of head and neck oncology. © 2025 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： visual analytics

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Leveraging Graph Theory for Advanced Embryo Stage Identification in Assisted Reproductive Technologies 47th

Leveraging Graph Theory for Advanced Embryo Stage Identifica...

引用

47th Mexican conference on Biomedical Engineering

作者： Munoz-Herrera, Saul Paredes, Omar Univ Guadalajara Biodigital Innovat Lab CUCEI Guadalajara Mexico IVF 2 0 Ltd London England

ISBN: (纸本)9783031821226;9783031821233

In recent years, the use of graph theory in image analysis has gained traction, offering a flexible approach to handling complex data. This study explores the application of graph-based clustering techniques to embryo images captured during various developmental stages. We represent these images as graphs, where nodes correspond to enriched features extracted from image patches, and edges are established based on proximity and visual similarities. Dimensionality reduction was performed using Principal Component analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE), followed by clustering using algorithms such as KMeans, Agglomerative Clustering, Gaussian Mixture Models (GMM), Spectral Clustering, and Birch. Our results indicate that GMM outperformed other methods, achieving the highest scores in metrics such as Adjusted Rand Index (0.1673), Normalized Mutual Information (0.2455), Homogeneity (0.2443), Completeness (0.2467), and v-Measure (0.2455), along with a strong Silhouette Score (0.4026). Notably, significant clustering tendencies were observed in the tB and tPN stages, while other stages exhibited a more mixed distribution, particularly in the tn and tSC stages. This research not only pioneers the use of graph-based methods in embryology but also suggests the potential for future improvements through the integration of advanced deep learning techniques and the expansion of data sets. The findings contribute significantly to the field of reproductive medicine, providing new tools for the analysis and classification of embryonic development stages.

关键词： Graph-Based data Representation Embryo Image analysis Image-Based Network Generation Clustering Algorithms

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Real Time Phishing Detection Using Lexical analysis and visual Similarity 14th

Real Time Phishing Detection Using Lexical Analysis and Vis...

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14th EAI International conference on Broadband Communications, Networks, and Systems, BROADNETS 2024

作者： Gnanesh, A. Deepesh, Dasa A. Hegde, Bhargav vyasamudri, Shreehari Sarasvathi, v. PES University Bengaluru560100 India

ISBN: (纸本)9783031811678

Phishing, a form of social engineering, involves deceptive practices to extract sensitive information from individuals. Typically, attackers manipulate their messages to mimic genuine communication from reputable entities like financial institutions, social networks, or online marketplaces. Phishing attempts manifest across various communication channels, encompassing email, text messages, and social media platforms. The acquired sensitive data fuels identity theft and financial fraud, underscoring the importance of vigilance when encountering unsolicited communications or hyperlinks soliciting personal information or immediate action. This paper offers a comprehensive approach to tackle phishing hazards, employing diverse features including URL structure for lexical analysis and screen-shot for visual similarity using transfer learning. Notably, the XGBoostClassifier attains an outstanding accuracy rate of 96.89%. To bolster this, a hybrid approach is adopted, integrating the MobileNet model for visual similarity-based detection. The incorporation of the MobileNet model introduces a visual similarity-based detection layer, augmenting the system’s capabilities. Implemented as a Chrome plug-in, this system dynamically scrutinizes website URLs, promptly alerting users about potential phishing threats. Rigorous testing on real-world phishing websites showcases the method’s robust performance, offering a reliable and user-friendly solution to detect and prevent phishing attacks. The hybrid integration of feature based detection through XGBoostClassifier and visual similarity analysis using MobileNet fortifies the system, elevating its effectiveness in safeguarding against evolving phishing assaults. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Phishing

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Elaborating visual Firm-Generated Content to Enhance the Customer Journey

Elaborating Visual Firm-Generated Content to Enhance the Cus...

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International conference on Marketing and Technologies, ICMarkTech 2023

作者： Lapresta-Romero, Sara Hernández-Ortega, Blanca University of Zaragoza Gran Vía 2 Zaragoza50005 Spain

ISBN: (纸本)9789819736973

visual-based social networks highlight the importance of generating an adequate visual firm-generated content, which promotes new interactions focused on ephemeral formats. This study aims to examine visual firm-generated content published on ephemeral content on social networks and its role in the extension of the customer journey. We recognize four elements that cover the whole of post design: brand cohesiveness, authenticity, informativeness, and emotionality. We elaborate a dataset from a prominent operator of tourism resorts in Europe consisting of 525 Instagram stories published between February and March 2019. data are examined and structured by observation. We use Artificial Intelligence (AI) and computerized text analysis tools to evaluate the content. We develop a two-equation seemingly unrelated regression (SUR) model. Our results show that brand cohesiveness, authenticity, and informativeness positively influence the extension of customer journey. Our findings support brand managers in creating successful visual firm-generated content for the extension of customer journeys on social networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sales

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Predicting Box Office Success: A Transformer-Based Multi-Modal Approach 4

Predicting Box Office Success: A Transformer-Based Multi-Mod...

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4th International conference on Sentiment analysis and Deep Learning, ICSADL 2025

作者： Jose, R. Arul Krishnan, R. Santhana Penyameen, K. Raj, J. Relin Francis Kumar, v. vinoth Priya, M. Rajarajeswari College of Engineering Department of Electrical and Electronics Engineering Bengaluru India Scad College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Velammal College of Engineering and Technology Department of Information Technology Madurai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Psna College of Engineering and Technology Department of Information Technology Dindigul India

ISBN: (纸本)9798331523923

This research presents a Transformer-based multi-modal architecture for predicting box office revenue by integrating diverse data sources: text, visuals, and numerical features. The proposed framework leverages RoBERTa for textual data such as movie descriptions, reviews, and scripts, vision Transformers (viT) for visual data including posters and trailers, and MLPs for numerical data like budget, genre, and actor popularity. A cross-attention mechanism is employed to fuse multi-modal embeddings, enabling comprehensive analysis and accurate predictions. The model is trained using PyTorch, optimized with AdamW, and enhanced by data augmentation and TPUs for efficiency. Performance is evaluated using metrics like MAE, RMSE, and R2. Deployment on AWS via FastAPI ensures scalable access, with SHAP explainability providing insights into model decisions. This system offers a robust and interpretable solution for predicting box office performance, catering to the evolving needs of the entertainment industry. © 2025 IEEE.

关键词： Budget control

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