Daniel M. Herzig
- Computer Science Applications top 10%
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- Data Quality and Management 5
- Artificial Intelligence top 10%
- Semantic Web and Ontologies 12
- Topic Modeling 3
- Information Systems top 5%
- Web Data Mining and Analysis 6
- Information Retrieval and Search Behavior 2
- Library Science and Information Systems 1
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- Data Management and Algorithms 4
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- Manufacturing Process and Optimization 1
- Co-authors
- Peter MikaJeffrey PoundRoi BlancoHarry HalpinHenry S. ThompsonPeter HaaseThanh TranAndriy Nikolov
- Cited by
- Computer Science ApplicationsManagement Science and Operations ResearchArtificial Intelligence
- Partner nations
- GermanyUnited KingdomSpain
In The Last Decade
Daniel M. Herzig
14 papers receiving 233 citations
Peers
Comparison fields: 5 of 39
- Computer Science Applications 43
- Management Science and Operations Research 84
- Artificial Intelligence 201
- Information Systems 111
- Signal Processing 25
Countries citing papers authored by Daniel M. Herzig
This map shows the geographic impact of Daniel M. Herzig'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 Daniel M. Herzig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel M. Herzig more than expected).
Fields of papers citing papers by Daniel M. Herzig
This network shows the impact of papers produced by Daniel M. Herzig. 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 Daniel M. Herzig. The network helps show where Daniel M. Herzig may publish in the future.
Co-authorship network
The 17 scholars most cited alongside Daniel M. Herzig, 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 | 2019 | 39 | |
| 2 | Use Cases of the Industrial Knowledge Graph at Siemens. | 2018 | 20 |
| 3 | 2018 | 2 | |
| 4 | Alexa, Ask Wikidata! Voice Interaction with Knowledge Graphs using Amazon Alexa. | 2017 | 2 |
| 5 | Planungsdaten schnell finden und einfach nutzen: Linked Open Data und semantische Suche im Einsatz für das KTBL-Datenangebot | 2014 | 0 |
| 6 | 2014 | 3 | |
| 7 | 2013 | 17 | |
| 8 | 2013 | 0 | |
| 9 | 2012 | 11 | |
| 10 | 2012 | 15 | |
| 11 | One query to bind them all | 2011 | 2 |
| 12 | Entity Search Evaluation over Structured Web Data | 2011 | 31 |
| 13 | 2011 | 23 | |
| 14 | 2011 | 57 | |
| 15 | Multilingual Expert Search using Linked Open Data as Interlingual Representation. | 2010 | 1 |
| 16 | Evaluating Ad-Hoc Object Retrieval | 2010 | 29 |
About Daniel M. Herzig
Daniel M. Herzig is a scholar working on Management Science and Operations Research, Artificial Intelligence and Signal Processing, having authored 16 papers that have together received 252 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (12 papers), Web Data Mining and Analysis (6 papers), Data Quality and Management (5 papers), Data Management and Algorithms (4 papers), Topic Modeling (3 papers), Information Retrieval and Search Behavior (2 papers), Manufacturing Process and Optimization (1 paper) and Library Science and Information Systems (1 paper). The work is most often cited by research in Computer Science Applications (43 citations), Management Science and Operations Research (84 citations) and Artificial Intelligence (201 citations). Daniel M. Herzig has collaborated with scholars based in Germany, United Kingdom and Spain. Frequent co-authors include Peter Mika, Jeffrey Pound, Roi Blanco, Harry Halpin, Henry S. Thompson, Peter Haase, Thanh Tran, Thanh Tran, Andriy Nikolov and Günter Ladwig. Their work appears in journals such as Journal of Web Semantics, Semantic Web, ACM SIGIR Forum, Repository KITopen (Karlsruhe Institute of Technology) and SSRN Electronic Journal.
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.