Daniel Krause

1.0k citations
34 papers · 391 indexed · h-index 10

Daniel Krause

30 papers receiving 364 citations

Peers

Daniel Krause
Comparison fields: 5 of 53
  • Computer Science Applications 53
  • Information Systems 196
  • Signal Processing 91
  • Artificial Intelligence 166
  • Statistical and Nonlinear Physics 51
Replace Jae‐wook Ahn with:
Jae‐wook Ahn United States
Kumaripaba Athukorala Finland
Dominik Kowald Austria
Jack Muramatsu United States
Resa A. Roth United States
Marc Spaniol Germany
Clemens Drews United States
Steve Fox United States
Simon Dooms Belgium
Daniel J. Liebling United States
Daniel Krause relative to Jae‐wook Ahn United States Jae‐wook Ahn's profile →
Citations per field
00.5×6.2×
Jae‐wook Ahn · 1×
Citations per year

Countries citing papers authored by Daniel Krause

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Krause

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202411
2 20247
3 20239
4 20230
5 20234
6 20213
7 20210
8 2012136
9
RESEARCH ARTICLE Leveraging Search and Content Exploration by Exploiting Context in Folksonomy Systems
20100
10
Building Blocks for User Modeling with data from the Social Web.
20103
11
Recommend me a Service: Personalized Semantic Web Service Matchmaking.
20093
12
CONTEXT-AWARE RANKING ALGORITHMS IN FOLKSONOMIES
20090
13
A framework for flexible user profile mashups
20099
14
Mashing up user data in the Grapple User Modeling Framework
20091
15 20099
16
User Modeling and User Profile Exchange for SemanticWeb Applications.
20085
17 20086
18 20072
19
Personal Reader Agent: Personalized Access to Configurable Web Services
20069
20
User Profiling and Privacy Protection for a Web Service oriented Semantic Web
20062

About Daniel Krause

Daniel Krause is a scholar working on Signal Processing, Information Systems and Artificial Intelligence, having authored 34 papers that have together received 391 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (13 papers), Speech and Audio Processing (10 papers), Music and Audio Processing (9 papers), Semantic Web and Ontologies (9 papers), Web Data Mining and Analysis (6 papers), Service-Oriented Architecture and Web Services (6 papers), Peer-to-Peer Network Technologies (3 papers) and Speech Recognition and Synthesis (3 papers). The work is most often cited by research in Computer Science Applications (53 citations), Information Systems (196 citations) and Signal Processing (91 citations). Daniel Krause has collaborated with scholars based in Germany, Finland and Italy. Frequent co-authors include Fabian Abel, Nicola Henze, Eelco Herder, Geert‐Jan Houben, Archontis Politis, Konrad Kowalczyk, Evandro Costa, Julita Vassileva, Ig Ibert Bittencourt and Annamaria Mesaros. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, New Review of Hypermedia and Multimedia, IEEE Transactions on Learning Technologies, User Modeling and User-Adapted Interaction and Archives of Acoustics.

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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