Daniel M. Herzig

575 citations
21 papers · 452 · h-index 13

Impact in

Papers in

Daniel M. Herzig

20 papers receiving 422 citations

Peers

Daniel M. Herzig
Comparison fields: 5 of 54
  • Management Science and Operations Research 129
  • Artificial Intelligence 323
  • Computer Science Applications 53
  • Information Systems 205
  • Signal Processing 44
Replace Slava Novgorodov with:
Slava Novgorodov Israel
Nuno Silva Portugal
Sebastian Tramp Germany
Srividya Bansal United States
Michelle Cheatham United States
Catherine Faron Zucker France
Dmitry Mouromtsev Russia
Torsten Priebe Germany
Rose Dieng-Kuntz France
Jamie Taylor United States
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Citations per year

Countries citing papers authored by Daniel M. Herzig

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

The 22 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.

Border = papers with Daniel M. Herzig Line = papers co-authored together Daniel M. Herzig links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201175
2 200851
3
Entity Search Evaluation over Structured Web Data
201147
4 201946
5
Evaluating Ad-Hoc Object Retrieval
201043
6 200932
7 201130
8 201324
9
Use Cases of the Industrial Knowledge Graph at Siemens.
201823
10 201222
11 201316
12 201013
13 201212
14
Alexa, Ask Wikidata! Voice Interaction with Knowledge Graphs using Amazon Alexa.
20175
15
One query to bind them all
20113
16 20143
17
Multilingual Expert Search using Linked Open Data as Interlingual Representation.
20102
18 20182
19 20132
20 20111

About Daniel M. Herzig

Daniel M. Herzig is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Signal Processing and Computer Networks and Communications, having authored 21 papers that have together received 452 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (14 papers), Web Data Mining and Analysis (8 papers), Data Quality and Management (6 papers), Data Management and Algorithms (5 papers), Topic Modeling (3 papers), Information Retrieval and Search Behavior (3 papers), Advanced Database Systems and Queries (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Management Science and Operations Research (129 citations), Artificial Intelligence (323 citations), Computer Science Applications (53 citations), Information Systems (205 citations) and Signal Processing (44 citations). Daniel M. Herzig has collaborated with scholars based in Germany, Canada and Spain. Frequent co-authors include Peter Mika, Roi Blanco, Jeffrey Pound, Harry Halpin, Thanh Tran, Peter Haase, Henry S. Thompson, Thanh Tran, Andriy Nikolov and Günter Ladwig. Their work appears in journals such as Journal of Web Semantics, ACM SIGIR Forum, Semantic Web, Lecture notes in computer science 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.

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