Daniel Gruhl

9.0k citations
54 papers · 5.5k · 4 hit papers · h-index 19

Impact in

Papers in

    • Topic Modeling 14
    • Semantic Web and Ontologies 13
    • Natural Language Processing Techniques 12
    • Advanced Text Analysis Techniques 6
    • Web Data Mining and Analysis 14
    • Service-Oriented Architecture and Web Services 5

Daniel Gruhl

52 papers receiving 4.8k citations

Daniel Gruhl's Hit Papers

Steps toward a science of service systems 2007 · 706 citations
7060+10+20Years since publication50010001.5k

Peers

Daniel Gruhl
Comparison fields: 5 of 122
  • Computer Vision and Pattern Recognition 2.4k
  • Statistical and Nonlinear Physics 1.2k
  • Marketing 615
  • Information Systems 1.1k
  • Artificial Intelligence 1.3k
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Daniel Gruhl relative to Greg Linden United States Greg Linden's profile →
Citations per field
00.5×4.7×
Greg Linden · 1×
Citations per year

Countries citing papers authored by Daniel Gruhl

Since Specialization
Citations

This map shows the geographic impact of Daniel Gruhl'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 Gruhl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Gruhl more than expected).

Fields of papers citing papers by Daniel Gruhl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Gruhl. 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 Gruhl. The network helps show where Daniel Gruhl may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Gruhl, 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 Gruhl Line = papers co-authored together Daniel Gruhl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Techniques for data hiding
Hit paper breakdown →
19961901
2
Information diffusion through blogspace
Hit paper breakdown →
2004730
3
Steps toward a science of service systems
Hit paper breakdown →
2007706
4
Information diffusion through blogspace
Hit paper breakdown →
2004649
5 1995339
6 2003282
7 2005280
8 200375
9 200073
10 200464
11 200355
12 201737
13 200833
14 200132
15 200430
16 201226
17 200224
18 200223
19 201918
20 201013

About Daniel Gruhl

Daniel Gruhl is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Management Science and Operations Research and Molecular Biology, having authored 54 papers that have together received 5.5k indexed citations. Recurring topics across this work include Web Data Mining and Analysis (14 papers), Topic Modeling (14 papers), Semantic Web and Ontologies (13 papers), Natural Language Processing Techniques (12 papers), Data Quality and Management (7 papers), Advanced Database Systems and Queries (6 papers), Advanced Text Analysis Techniques (6 papers) and Service-Oriented Architecture and Web Services (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.4k citations), Statistical and Nonlinear Physics (1.2k citations), Marketing (615 citations), Information Systems (1.1k citations) and Artificial Intelligence (1.3k citations). Daniel Gruhl has collaborated with scholars based in United States, Israel and Japan. Frequent co-authors include Walter Bender, Norishige Morimoto, Andrew Tomkins, R. Guha, David Liben‐Nowell, Jim Spohrer, Paul P. Maglio, J. Bailey, Jasmine Novak and Ravi Kumar. Their work appears in journals such as IBM Systems Journal, Journal of Web Semantics, Journal of Grid Computing, Computer and Communications of the ACM.

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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