检索结果-内蒙古大学图书馆

News Ninja: Gamified Annotation of Linguistic Bias in Online News

Proceedings of the ACM on human-computer interaction 2024年第CHI PLAY期8卷 1-29页

作者： Hinterreiter, Smi Spinde, Timo Oberdörfer, Sebastian Echizen, Isao Latoschik, Marc Erich Human-Computer Interaction Group University of Würzburg Würzburg Germany Scientific Information Analytics Group University of Göttingen Göttingen Germany Information and Society Research Division National Institute of Informatics Tokyo Japan

Recent research shows that visualizing linguistic bias mitigates its negative effects. However, reliable automatic detection methods to generate such visualizations require costly, knowledge-intensive training data. To facilitate data collection for media bias datasets, we present News Ninja, a game employing data-collecting game mechanics to generate a crowdsourced dataset. Before annotating sentences, players are educated on media bias via a tutorial. Our findings show that datasets gathered with crowdsourced workers trained on News Ninja can reach significantly higher inter-annotator agreements than expert and crowdsourced datasets with similar data quality. As News Ninja encourages continuous play, it allows datasets to adapt to the reception and contextualization of news over time, presenting a promising strategy to reduce data collection expenses, educate players, and promote long-term bias mitigation. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Data collection

来源：评论

学校读者我要写书评

暂无评论

visual analytics for Decision-Making

Visual Analytics for Decision-Making

引用

International Conference on Information visualisation (IV)

作者： Kawa Nazemi Cristian A. Secco Lennart B. Sina Uliana Eliseeva Elena Correll Midhad Blazevic Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

ISBN: (数字)9798350380163

ISBN: (纸本)9798350380170

visual analytics combines human cognitive processes and abilities with computational models to solve complex problems by using the strengths of computers and humans. Decision-making processes are commonly very complex and involve investigating various factors and indicators. By integrating visual analytics into the decision-making process, the human cognitive load can be reduced, and the accuracy of decisions could be higher. This might be why many visual decision support systems exist, and visual analytics approaches provide decision support. However, the literature review reveals that there are either structured decision support methods integrating statistical approaches or visual analytics methods that are commonly designed for exploration, comparison, and analysis to support decision-making. By investigating the core ideas related to human limitations and programmed decision-making, we propose in this paper a novel visual analytics approach to support structured and exploratory approaches by integrating Multi-Criteria Decision Making (MCDM) methods in visual analytics. To reduce the common expert judgment in such methods, our approach trains a neural network through the interaction with the system. Our contributions are threefold: providing a systematic view of decision-making processes, discussing the dual paradigms of visual decision support systems, and proposing a visual analytics approach that leverages MCDM and neural networks for improved decision support.

关键词： Decision support systems Training Accuracy Cognitive processes visual analytics Refining Neural networks computer architecture MCDM Testing

来源：评论

学校读者我要写书评

暂无评论

Query-to- Vis: Conceptualization of a Broad-coverage Automated visualization Pipeline

Query-to- Vis: Conceptualization of a Broad-coverage Automat...

引用

International Conference on Information visualisation (IV)

作者： Uliana Eliseeva Simon Heiß Kawa Nazemi Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

ISBN: (数字)9798350380163

ISBN: (纸本)9798350380170

Automated visualization generation tools make visualization authoring more accessible to non-programmers and accelerate expert visualization designers in their work. Yet, combining these functions in one system remains a challenge for the research community because it has to maintain a high level of expressiveness and facilitate several tasks for diverse background users while remaining simple and intuitive. Providing a system that handles multiple tasks for heterogeneous user groups could be achieved, on the one hand, through unrestricted user input in the form of natural language. On the other hand, introducing a certain level of abstraction on multiple levels of the system can help integrate more tasks than implementing them separately. In this work, we present the concept of such a system with an LLM-based user query handling and mapping of the extracted components of the user task onto visual design choices with the help of deep learning. Our trained neural network shows promising results, suggesting the generalizability of the proposed approach.

关键词： Deep learning visualization Pipelines Neural networks Natural languages Diversity reception

来源：评论

学校读者我要写书评

暂无评论

Medical visual analytics - An Interactive Approach for Analyzing Electronic Health Records

Medical Visual Analytics - An Interactive Approach for Analy...

引用

International Conference on Information visualisation (IV)

作者： Cristian A. Secco Lennart B. Sina Kawa Nazemi Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

ISBN: (数字)9798350380163

ISBN: (纸本)9798350380170

The evolving digitization of Germany's medical care provides new opportunities for computer-supported patient treatment. Particularly, resident medical doctors can be empowered to gather comprehensive information about the disease history, medications, and other important indicators quickly and increase the quality of treatment while maintaining the time for treatment. The central element that enables such computer-assisted support in the treatment is electronic health records (EHRs). EHRs facilitate digital access to vast medical data repositories in digital format that were previously confined to analog forms in medical facilities. However, using EHRs in daily medical treatment is time-consuming due to their unstructured textual format. There is a pressing need for analytical tools that extract the most important information from EHRs, provide that information in a quickly comprehensible way, and synthesize the entire patient history for a reliable medical treatment. In this work, we propose an innovative visual analytics approach and system specifically designed for medical care. Our approach and the implemented system seamlessly integrate interactive visualizations with fitting pre-trained transformer models to assist medical professionals in consolidating and presenting intricate patient data through comprehensible interactive visual interfaces. Utilizing transformer-based information extraction, it carefully manages the shift from digitized medical documents to quickly accessible patient information in a dynamic and interactive visual interface.

关键词： visual analytics Medical treatment Data visualization Pressing Transformers Information retrieval History Data mining Reliability Electronic medical records

来源：评论

学校读者我要写书评

暂无评论

visual analytics - Climate Change in Social Media

Visual Analytics - Climate Change in Social Media

引用

International Conference on Information visualisation (IV)

作者： Vanessa Kokoschka Cristian A. Secco Kawa Nazemi Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

ISBN: (数字)9798350380163

ISBN: (纸本)9798350380170

Climate change is one of the greatest challenges of our time and affects all areas of our society. Climate science is a complex field and the majority of the public does not experience the effects of climate change directly but through media. Social media platforms are among the most important communication channels: millions of people exchange information and interact with content on these platforms every day. For this reason, knowledge about the development of climate communication is relevant for various disciplines, but especially for communication sciences. How social media users interact with content on climate change and what content they consume is important for adapting communication strategies. This enables communicators such as journalists to respond appropriately to user interests and align their content. We contribute with a novel approach to portray climate change behavior of social media, transformer-based speech extraction from web video, transformer-based information extraction and trend analysis, and an interactive visual interface showing topic-specific data and trends.

关键词： Climate change visual analytics Social networking (online) Video on demand Market research Data visualization Metadata visual analytics Meteorology

来源：评论

学校读者我要写书评

暂无评论

visual analytics for Interactive Machine Learning - A Modular Multi-View Approach

Visual Analytics for Interactive Machine Learning - A Modula...

引用

International Conference on Information visualisation (IV)

作者： Elena Correll Uliana Eliseeva Kawa Nazemi Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

ISBN: (数字)9798350380163

ISBN: (纸本)9798350380170

Interactive machine learning enhances data pre-processing, feature engineering, and modeling through human interactions. As interactive machine learning becomes more in-corporated into visual analytics, new pipelines, concepts, and task taxonomies rise. A common technique for managing complexity in visual analytic systems is multiple-linked views. By now no comprehensive concept exists for multiple-linked views across all stages of the visual analytic pipeline. Therefore, we introduce a conceptual model that shows the possible interactions between humans and computers at each step of the VA pipeline. Our main contribution is a coordination model for linking multiple views across each layer of the VA pipeline.

关键词： computers Analytical models visual analytics Computational modeling Pipelines Taxonomy Refining Decision making Machine learning Data models

来源：评论

学校读者我要写书评

暂无评论

visual analytics for Forecasting Technological Trends from Text

Visual Analytics for Forecasting Technological Trends from T...

引用

International Conference on Information visualisation (IV)

作者： Cristian A. Secco Lennart B. Sina Midhad Blazevic Kawa Nazemi Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

Knowledge of emerging and declining trends and their potential future course is highly relevant in many application domains, particularly in corporate strategy and foresight. The early awareness of trends allows reacting to market, political, and societal changes and challenges at an appropriate time. In our previous works, we presented approaches for the early identification and analysis of emerging trends. Although our previous approaches are detecting emerging trends appropriately, they lack the ability to predict the potential future course of a trend or technology. We present in this work a novel visual analytics approach for forecasting emerging trends that combines interactive visualizations with machine learning techniques and statistical approaches to detect, analyze, and predict trends from textual data. We extend our previous work on analyzing technological trends from text and propose an advanced approach that includes forecasting through hybrid techniques consisting of neural networks and established statistical methods. Our approach offers insights from enormous data sets and the potential future course of trends based on their occurrence in textual data. We contribute with a novel approach for identifying and forecasting trends, a hybrid forecasting method to predict trends from text, and interactive visualization techniques on macro level, micro level, and monitoring topics of interest.

关键词：

来源：评论

学校读者我要写书评

暂无评论

visual analytics for Corporate Foresight - A Conceptual Approach

Visual Analytics for Corporate Foresight - A Conceptual Appr...

引用

International Conference on Information visualisation (IV)

作者： Lennart B. Sina Cristian A. Secco Midhad Blazevic Kawa Nazemi Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

Corporate Foresight is a strategic planning process that helps organizations anticipate and prepare for future trends and developments that may impact their operations. It involves analyzing data, identifying potential scenarios, and creating strategies to address them to ensure long-term success and sustainability. visual analytics approaches have been introduced to cover parts of the Corporate Foresight process. These concepts present different approaches to integrate machine learning methods and artificial intelligence with interactive visualizations to solve tasks such as identifying emerging trends. A holistic concept for synthesizing visual analytics with Corporate Foresight does not exist yet. We propose in this work a holistic visual analytics approach that covers the main aspects of Corporate Foresight by including strategic management and considers different organizational forms. Our model goes beyond the state-of-the-art by providing, besides foresight also, hindsight and insight. Our main contributions are the revised visual analytics model and its proof of concept through implementation as a web-based system with real data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence in visual analytics

Artificial Intelligence in Visual Analytics

引用

International Conference on Information visualisation (IV)

作者： Kawa Nazemi Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

visual analytics that combines automated methods with information visualization has emerged as a powerful approach to analytical reasoning. The integration of artificial intelligence techniques into visual analytics has enhanced its capabilities but also presents challenges related to interpretability, explainability, and decision-making processes. visual analytics may use artificial intelligence methods to provide enhanced and more powerful analytical reasoning capabilities. Furthermore, visual analytics can be used to interpret black-box artificial intelligence models and provide a visual explanation of those models. In this paper, we provide an overview of the state-of-the-art of artificial intelligence techniques used in visual analytics, focusing on both explainable artificial intelligence in visual analytics and the human knowledge generation process through visual analytics. We review explainable artificial intelligence approaches in visual analytics and propose a revised visual analytics model for Explainable artificial intelligence based on an existing model. We then conduct a screening review of artificial intelligence methods in visual analytics from two time periods to highlight recently used artificial intelligence approaches in visual analytics. Based on this review, we propose a revised task model for tasks in visual analytics. Our contributions include a state-of-the-art review of explainable artificial intelligence in visual analytics, a revised model for creating explainable artificial intelligence through visual analytics, a screening review of recent artificial intelligence methods in visual analytics, and a revised task model for generic tasks in visual analytics.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Recommendations in visual analytics - An Analytical Approach for Elaboration in Science

Recommendations in Visual Analytics - An Analytical Approach...

引用

International Conference on Information visualisation (IV)

作者： Midhad Blazevic Lennart B. Sina Cristian A. Secco Kawa Nazemi Department of Media & Department of Computer Science Human-Computer Interaction and Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

The huge amount of scientific content increases the workload for evaluating state-of-the-art research and the complexity of creating novel and innovative methods and approaches. Although many approaches exist using recommendations in various application domains, the full potential of recommendation systems is not yet fully utilized. Particularly, there are missing approaches that combine interactive visualizations with recommendation systems to enable an analytical investigation of the current state of technology and science. We, therefore, propose in this work a novel visual analytics approach that integrates recommendation methods as the model and provides a seamless integration of both interactive visualizations and recommendation systems. We utilize MAE and RMSE metrics and human validation to identify the best approach out of eight approaches that differ in vectorization and similarity algorithms to recommend scientific items. We contribute novel approaches for recommending scientific publications, venues, and projects, based on comparing traditional and deep-learning-based recommendation approaches. Furthermore, we propose a visual analytics approach that uses recommendation methods for analytical elaboration. This work shows the potential of integrating recommendation systems into scientific research and identifies potential future directions for improving the proposed model.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：