Victoria Yoon
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- Technology Adoption and User Behaviour 8
- Marketing top 5%
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- Big Data and Business Intelligence 6
- Information Systems top 5%
- Service-Oriented Architecture and Web Services 7
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- Semantic Web and Ontologies 14
- Multi-Agent Systems and Negotiation 10
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- Advanced Database Systems and Queries 6
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- Data Quality and Management 6
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- Digital Marketing and Social Media 5
- Co-authors
- Tor GuimãrãesZhiling GuoGuisseppi A. ForgionneHayden WimmerSarah M. RussellRichard RedmondManoj A. ThomasDapeng Liu
- Partner nations
- United StatesAustraliaHong Kong
In The Last Decade
Victoria Yoon
54 papers receiving 760 citations
Peers
Comparison fields: 5 of 91
- Information Systems and Management 236
- Marketing 196
- Management Information Systems 146
- Information Systems 201
- Organizational Behavior and Human Resource Management 85
Countries citing papers authored by Victoria Yoon
This map shows the geographic impact of Victoria Yoon's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Victoria Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Victoria Yoon more than expected).
Fields of papers citing papers by Victoria Yoon
This network shows the impact of papers produced by Victoria Yoon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Victoria Yoon. The network helps show where Victoria Yoon may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Victoria Yoon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 3 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 8 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 3 | |
| 6 | 2021 | 13 | |
| 7 | Analyzing the Impacts of Activation Functions on the Performance of Convolutional Neural Network Models | 2020 | 4 |
| 8 | 2020 | 15 | |
| 9 | 2020 | 11 | |
| 10 | Leveraging XBRL Calculation Linkbases to Overcome Semantic Heterogeneity across XBRL Fillings: The Multi-Ontology Multi-Concept Matrix (M3) | 2015 | 1 |
| 11 | 2015 | 1 | |
| 12 | 2014 | 23 | |
| 13 | 2011 | 95 | |
| 14 | The Semantic Web in Federated Information Systems: A Space Physics Case Study | 2010 | 4 |
| 15 | Moving Beyond Traditional Emergency Response Notification with VoiceXML | 2009 | 4 |
| 16 | Design Artifact to Support Knowledge-Driven Predictive and Explanatory Decision Analytics | 2006 | 2 |
| 17 | Heterogeneous Agent Development: A Multi-Agent System for Testing Stock Trading Algorithms | 2005 | 4 |
| 18 | A SEMANTIC APPROACH TO MONITOR BUSINESS PROCESS PERFORMANCE | 2005 | 16 |
| 19 | Natural Language Interface for a Multi Agent System | 2004 | 1 |
| 20 | 2002 | 1 |
About Victoria Yoon
Victoria Yoon is a scholar working on Management Information Systems, Information Systems and Management and Artificial Intelligence, having authored 57 papers that have together received 816 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (14 papers), Multi-Agent Systems and Negotiation (10 papers), Technology Adoption and User Behaviour (8 papers), Service-Oriented Architecture and Web Services (7 papers), Big Data and Business Intelligence (6 papers), Advanced Database Systems and Queries (6 papers), Data Quality and Management (6 papers) and Digital Marketing and Social Media (5 papers). The work is most often cited by research in Information Systems and Management (236 citations), Marketing (196 citations) and Management Information Systems (146 citations). Victoria Yoon has collaborated with scholars based in United States, Australia and Hong Kong. Frequent co-authors include Tor Guimãrães, Zhiling Guo, Guisseppi A. Forgionne, Hayden Wimmer, Sarah M. Russell, Richard Redmond, Manoj A. Thomas, Dapeng Liu, Vijayan Sugumaran and Stephen Russell.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.