检索结果-内蒙古大学图书馆

6th Collaborative European Research Conference, CERC 2020

作者： Below, Nicola Burkhardt, Dirk Kaupp, Lukas Nazemi, Kawa Darmstadt University of Applied Sciences Human-Computer Interaction and Visual Analytics Group Germany

Analytical Reasoning by applying machine learning approaches, artificial intelligence, NLP and visualizations allow to get deep insights into the different domains of various stakeholders and enable to solve complex tasks. Thereby the tasks are very heterogenous and subject of investigation in the different areas of application. These tasks or challenges should be defined by the stakeholders themselves and lead through a deep investigation to advanced analytical approaches. We therefore set up a strategic alliance of research, enterprises and societal organization with the goal of a strong collaboration to identify in a first step these challenges and workout technological solutions for each application scenario. We give in this paper a first draft of current challenges and technological advancements. The main contribution of this paper is next to an accurate description of the current challenges in the analytics domain, also the description of an agenda how these challenges can be solved. Furthermore, a process is explained, how the strategic alliance should act and organize their work to realize beneficial and useful analytical solutions. Copyright © 2020 for this paper by its authors.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

visual dashboards in trend analytics to observe competitors and leading domain experts 6

Visual dashboards in trend analytics to observe competitors ...

引用

6th Collaborative European Research Conference, CERC 2020

作者： Sina, Lennart Burkhardt, Dirk Nazemi, Kawa Darmstadt University of Applied Sciences Human-Computer Interaction and Visual Analytics Group Germany

The rapid change due to digitalization challenge a variety of market players and force them to find strategies to be aware of developments in these markets, particularly those that impact their business. The main challenge is what a practical solution could look like and how technology can support market players in these trend observation tasks. The paper outlines therefore a technological solution to observe specific authors e.g. researchers who influence a certain market or engineers of competitors. In many branches both are well-known groups to market players and there is almost always the need of a technology that supports the topical observation. This paper focuses on the concept of how a visual dashboard could enable a market observation and how data must be processed for it and its prototypical implementation which enables an evaluation later. Furthermore, the definition of a principal technological analysis for innovation and technology management is created and is also an important contribution to the scientific community that specifically considers the technology perspective and its corresponding requirements. Copyright © 2020 for this paper by its authors.

关键词： Commerce

来源：评论

学校读者我要写书评

暂无评论

A mobile visual analytics approach for instant trend analysis in mobile contexts 5

A mobile visual analytics approach for instant trend analysi...

引用

5th International Conference of the Virtual and Augmented Reality in Education, VARE 2019

作者： Burkhardt, Dirk Nazemi, Kawa Kuijper, Arjan Ginters, Egils Human-Computer Interaction and Visual Analytics Research Group Darmstadt University of Applied Sciences Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany Riga Technical University Riga Latvia

ISBN: (纸本)9788885741423

The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design. © 5th International Conference of the Virtual and Augmented Reality in Education, VARE 2019. All rights reserved.

关键词： Decision support systems

来源：评论

学校读者我要写书评

暂无评论

News Ninja: Gamified Annotation of Linguistic Bias in Online News

引用

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 Systematic Reviews According to PRISMA

Visual Analytics for Systematic Reviews According to PRISMA

引用

International Conference on Information visualisation (IV)

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

ISBN: (纸本)9781665490085

Systematic reviews play an essential role in various disciplines. Particularly, in biomedical sciences, systematic reviews according to a predefined schema and protocol are how related literature is analyzed. Although a protocol-based systematic review is replicable and provides the required information to reproduce each step and refine them, such a systematic review is time-consuming and may get complex. To face this challenge, automatic methods can be applied that support researchers in their systematic analysis process. The combination of artificial intelligence for automatic information extraction from scientific literature with interactive visualizations as a visual analytics system can lead to sophisticated analysis and protocoling of the review process. We introduce in this paper a novel visual analytics approach and system that enables researchers to visually search and explore scientific publications and generate a protocol based on the PRISMA protocol and the PRISMA statement.

关键词： Systematics Protocols visual analytics Face recognition Layout Data visualization Information retrieval

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 Collaboration - An Approach for visual Analytical Collaborative Research

Visual Collaboration - An Approach for Visual Analytical Col...

引用

International Conference on Information visualisation (IV)

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

ISBN: (纸本)9781665490085

Studies have shown that collaboration in scientific fields is rising and considered enormously important. However, collaboration has proved to be challenging for various reasons, among others, the requirements for human-machine workflows. The importance of scientific collaboration lies in the complexity of the challenges that are faced today. The more complex the challenge, the more scientists should work together. The current form of collaboration in the scientific community is not as intelligent as it should be. Scientists have to multitask with various applications, often losing cognitive focus. Collaboration itself is very nearsighted as it is usually conducted not solely based on expertise but instead on social or local networks. We introduce a single-source visual collaboration approach based on learning methods in this work. We use machine learning and natural language processing approaches to improve the traditional research and development process and create a system that facilitates and encourages collaboration based on expertise, enhancing the research collaboration process in many ways. Our approach combines collaborative visual analytics with enhanced collaboration techniques to support researchers from different disciplines.

关键词： Learning systems visualization visual analytics Collaboration Machine learning Feature extraction Natural language processing

来源：评论

学校读者我要写书评

暂无评论

Comparison of Full-text Articles and Abstracts for visual Trend analytics through Natural Language Processing

Comparison of Full-text Articles and Abstracts for Visual Tr...

引用

International Conference on Information visualisation (IV)

作者： Kawa Nazemi Maike J. Klepsch Dirk Burkhardt Lukas Kaupp Human-Computer Interaction & Visual Analytics Darmstadt University of Applied Sciences Darmstadt Germany

ISBN: (数字)9781728191348

ISBN: (纸本)9781728191355

Scientific publications are an essential resource for detecting emerging trends and innovations in a very early stage, by far earlier than patents may allow. Thereby visual analytics systems enable a deep analysis by applying commonly unsupervised machine learning methods and investigating a mass amount of data. A main question from the visual analytics viewpoint in this context is, do abstracts of scientific publications provide a similar analysis capability compared to their corresponding full-texts? This would allow to extract a mass amount of text documents in a much faster manner. We compare in this paper the topic extraction methods LSI and LDA by using full text articles and their corresponding abstracts to obtain which method and which data are better suited for a visual analytics system for Technology and Corporate Foresight. Based on a easy replicable natural language processing approach, we further investigate the impact of lemmatization for LDA and LSI. The comparison will be performed qualitative and quantitative to gather both, the human perception in visual systems and coherence values. Based on an application scenario a visual trend analytics system illustrates the outcomes.

关键词： Information science visual analytics Coherence Market research Large scale integration Natural language processing Libraries

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

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：