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13th Annual ACM International Conference on Web Search and Data Mining (WSDM)

作者： Wei, Jiaqi Han, Shuo Zou, Lei Peking Univ Beijing Peoples R China

ISBN: (纸本)9781450368223

Large scale knowledge graph (KG) has attracted wide attentions in both academia and industry recently. However, due to the complexity of SPARQL syntax and massive volume of real KG, it remains difficult for ordinary users to access KG. In this demo, we present VISION-KG, a topic-centric visualization system to help users navigate KG easily via entity summarization and entity clustering. Given a query entity v(0), VISION-KG summarizes the induced subgraph of v(0)'s neighbor nodes via our proposed facts ranking method that measures importance, relatedness and diversity. Moreover, to achieve conciseness, we split the summarized graph into several topic-centric summarized subgraph according to semantic and structural similarities among entities. We will demonstrate how VISION-KG provides a user-friendly visualization interface for navigating KG.

关键词： knowledge graph visualization entity summarization entity clustering topic-centric

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Semantic Maps for knowledge graphs: A Semantic-Based Summarization Approach

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IEEE ACCESS 2024年 12卷 6729-6744页

作者： Camarillo-Ramirez, Pablo Cervantes-Alvarez, Francisco Gutierrez-Preciado, Luis Fernando Western Inst Technol & Higher Educ Guadalajara 45601 Jalisco Mexico

knowledge graphs (KGs) have emerged as a powerful tool for representing semantic structured information and enabling the development of intelligent systems. This paper focuses on the generation of semantic maps as summarization method for KGs. We propose a strategy that utilizes centroid-based clustering algorithms, namely Affinity Propagation and Partitioning Around Medoids (PAM), to capture the semantic distance between nodes in the KG and generate meaningful clusters. Our experiments demonstrate divergent results between the two clustering algorithms, with Affinity Propagation showing qualitative coherence and meaningfulness, while PAM performs well in terms of internal validation metrics. We leverage the computed centroids to infer a main term of the semantic map, which contributes to the visually appealing and informative representation of the KG. The combination of semantic distance capture, clustering algorithms, and centroid-based inference facilitates a comprehensive understanding of the KG. Our findings highlight the importance of considering both qualitative and quantitative evaluation measures in assessing clustering results. The effectiveness of semantic maps is showcased in visualizing KGs and advancing the field of knowledge graph visualization. The integration of centroid-based clustering algorithms, qualitative evaluation, and inference methods offers improved clarity and interpretability for complex KG analysis.

关键词： Semantics knowledge graphs visualization Clustering algorithms Data visualization Ontologies Measurement knowledge graph visualization semantic distance semantic mapping visual data exploration clustering

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Ginkgo-P: General Illustrations of knowledge graphs for Openness as a Platform 24

Ginkgo-P: General Illustrations of Knowledge Graphs for Open...

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17th ACM International Conference on Web Search and Data Mining (WSDM)

作者： Hill, Blaine Liu, Lihui Tong, Hanghang Univ Illinois Dept Comp Sci Urbana IL 61801 USA

ISBN: (纸本)9798400703713

Accessibility and openness are two of the most important factors in motivating AI and Web research. One example is as costs to train and deploy large knowledge graph (KG) systems increases, valuable auxiliary features such as visualization, explainability, and automation are often overlooked, diminishing impact and popularity. Furthermore, current KG research has undergone a vicissitude to become convoluted and abstract, dissuading collaboration. To this end, we present Ginkgo-P, a platform to automatically illustrate any KG algorithm with nothing but a script and a data file. Additionally, Ginkgo-P elucidates modern KG research on the UMLS dataset with interactive demonstrations on four categories: KG Node Recommendation, KG Completion, KG Question Answering, and KG Reinforcement Learning. These categories and their many applications are increasingly ubiquitous yet lack both introductory and advanced resources to accelerate interest and contributions: with just a few clicks, our demonstration addresses this by providing an open platform for users to integrate individual KG algorithms. The source code for Ginkgo-P is available: we hope that it will propel future KG systems to become more accessible as an open source project.

关键词： knowledge graph Reasoning knowledge graph visualization knowledge graph Systems knowledge graph Accessibility

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SocioPedia: Visualizing Social knowledge Over Time 23

SocioPedia: Visualizing Social Knowledge Over Time

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38th Annual ACM Symposium on Applied Computing (ACM SAC)

作者： Nguyen, Tra My Jung, Jason J. Chung Ang Univ Dept Comp Engn Seoul South Korea

ISBN: (纸本)9781450395175

In this paper, we introduce SocioPedia, which is a real-time automatic system for efficiently visualizing and analyzing the variations, characteristics, and evolutions of social knowledge following the change of time. SocioPedia has been developed to provide a full knowledge graph life cycle and combined the temporal information into each processed knowledge. To benefit different classes of users, SocioPedia provides a user-friendly and intuitive environment with different visualization types including static knowledge visualization, timeline knowledge visualization, timeline characteristic visualization, and dynamic timeline visualization.

关键词： knowledge graph knowledge graph visualization sociopedia

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CiteSpace-based Commodity Trading Risk Research Status and Trend Analysis

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Procedia Computer Science 2024年 242卷 1362-1369页

作者： Wanlin Xie Xiaoyan Gu Shuo Cui Xingfen Wang School of Information Management Bei Jing Information Science & Technology University Beijing 100192 China

Commodities play a pivotal role in the global economy, and their dramatic price fluctuations can affect national security and global economic stability. This paper focus on the field of commodities, utilizing the Web of Science and CNKI databases. Based on the CiteSpace knowledge graph visualization analysis tool, it conducts a bibliometric analysis of the Chinese and English literature on commodity risk published from 2004 to 2023, aiming to reveal the keywords, emerging trends, major research institutions and their collaborative networks, trends in the issuance of articles, and major contributing countries, and authors. This analysis provides insights into the academic landscape of commodity risk and helps to identify future research directions.

关键词： commodity trading risk CiteSpace knowledge graph visualization analysis

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ARViz: Interactive visualization of Association Rules for RDF Data Exploration 25

ARViz: Interactive Visualization of Association Rules for RD...

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25th International Conference Information Visualisation (IV) - AI and Visual Analytics and Data Science

作者： Menin, Aline Cadorel, Lucie Tettamanzi, Andrea Giboin, Alain Gandon, Fabien Winckler, Marco Univ Cote Azur INRIA CNRS I3S UMR 7271 Nice France

ISBN: (纸本)9781665438278

Association rule mining often leads the analyst into a rough rummaging process to identify rules that are relevant to understand specific problems. We propose a visualization interface to assist the rule selection process and evaluate it on an RDF knowledge graph derived from the COVID-19 Open Research Dataset. The user interface supports data exploration with focus on the overview of rules through a scatter plot, subsets of rules through a chord diagram chart, and itemsets through an association graph which is dynamically created by entering an item of interest (i.e. a named entity). Further, the analyst can interactively recover a list of publications containing the named entities involved in a particular rule. Among the original aspects of our approach, we highlight the representation of attributes describing measures of interest (i.e. confidence and interestingness), a visual indication of existence (or not) of symmetry in association rules, the exploration of subsets of rules according to clusters of publications and named entities, and an interactive prompting that aims at expanding the discovery of named entities within selected association rules. We assess our approach through a semi-structured interview involving experts in the domains of data mining and biomedicine, whose feedback could assist the refinement of the visual and interaction tools.

关键词： association rule mining interactive visualization knowledge graph visualization RDF visualization COVID-19

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A Government Policy Analysis Platform Based on knowledge graph 2

A Government Policy Analysis Platform Based on Knowledge Gra...

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2nd International Conference on Artificial Intelligence and Big Data (ICAIBD)

作者： Wang, Peng Li, Zesong Li, Zeyuan Fang, Xin CETC Big Data Res Inst Co Ltd Guiyang Peoples R China

ISBN: (纸本)9781728108315

To develop government governance, government departments promote government information publicity actively in recent years. As an important part of government information, policies are published in the information disclosure guide on government's websites, which provide convenience for citizens and organizations to look up. However, when the government provides massive multi-source policy information, it also brings the problem of information overload. In view of the difficulty in the public inquiry, comprehension, and analysis of policy, this paper designed and developed a policy analysis platform based on the knowledge graph, aiming to provide information support for the government information disclosure. Employing technology of knowledge graph, the platform can process vast amounts of data. We also build a resource description system and a graph model to extract and store the feature of policy information. Then using visualizing human-computer interaction mode of exploratory analysis, we can achieve accurate and efficient policy information search, and policy analysis. The platform provides more convenience for the public to fully understand the content of policies by comprehensively combing the content, revealing policies' characteristics and mining their relationship.

关键词： knowledge graph connections analysis policy big data knowledge extraction knowledge graph visualization

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Wiki'ike: Making Use of knowledge graphs in a Classroom 18

Wiki'ike: Making Use of Knowledge Graphs in a Classroom

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ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW)

作者： Mirhosseini, Moeen Seo, Jiwon MyMusicTaste Seoul South Korea Hanyang Univ Dept Comp Sci Seoul South Korea

ISBN: (纸本)9781450360180

We demonstrate Wiki'ike, a system that helps exploration of knowledge graphs (KGs). Wiki'ike takes advantage of location and temporal information for easy exploration of KGs. We present how Wiki'ike can be used in a classroom to help teachers motivate students and communicate knowledge efficiently. In our demonstration, we show two scenarios where Wiki'ike can be used in a classroom for teaching history and geography. In the two scenarios, Wiki'ike helps inspire students curiosity and communicate knowledge in various perspectives.

关键词： knowledge graph visualization Computer Aided Teaching

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