Anne Schuth

1.1k citations
28 papers · 463 · h-index 12

Impact in

Papers in

    • Information Retrieval and Search Behavior 13
    • Expert finding and Q&A systems 5
    • Web Data Mining and Analysis 5
    • Topic Modeling 8
    • Natural Language Processing Techniques 4
    • Semantic Web and Ontologies 4
    • Advanced Text Analysis Techniques 3

Anne Schuth

26 papers receiving 427 citations

Peers

Anne Schuth
Comparison fields: 5 of 56
  • Computer Science Applications 72
  • Communication 71
  • Information Systems 224
  • Artificial Intelligence 195
  • Management Science and Operations Research 69
Replace Ajita John with:
Ajita John United States
Udo Kruschwitz United Kingdom
Alicia Iriberri United States
Manos Tsagkias Netherlands
Dolf Trieschnigg Netherlands
Ke Zhou United Kingdom
Besnik Fetahu Germany
Thomas Norton United States
Sergej Zerr Germany
Norman Meuschke Germany
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Citations per field
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Citations per year

Countries citing papers authored by Anne Schuth

Since Specialization
Citations

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

Fields of papers citing papers by Anne Schuth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Anne Schuth, 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 Anne Schuth Line = papers co-authored together Anne Schuth links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017141
2 201363
3 201642
4 200739
5 201427
6 201321
7 201519
8 201515
9 201314
10
Overview of the INEX 2012 Linked Data Track
201214
11 201412
12 201511
13
DutchParl. The Parliamentary Documents in Dutch
201010
14 20145
15 20145
16 20194
17 20233
18 20173
19
Overview of the TREC 2016 Open Search track
20163
20 20163

About Anne Schuth

Anne Schuth is a scholar working on Information Systems, Artificial Intelligence, Computer Science Applications, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 28 papers that have together received 463 indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (13 papers), Topic Modeling (8 papers), Mobile Crowdsensing and Crowdsourcing (7 papers), Expert finding and Q&A systems (5 papers), Web Data Mining and Analysis (5 papers), Natural Language Processing Techniques (4 papers), Semantic Web and Ontologies (4 papers) and Advanced Text Analysis Techniques (3 papers). The work is most often cited by research in Computer Science Applications (72 citations), Communication (71 citations), Information Systems (224 citations), Artificial Intelligence (195 citations) and Management Science and Operations Research (69 citations). Anne Schuth has collaborated with scholars based in Netherlands, United Kingdom and United States. Frequent co-authors include Maarten de Rijke, M. Marx, Shimon Whiteson, Martijn Spitters, Katja Hofmann, Harrie Oosterhuis, Aleksandr Chuklin, Filip Radlinski, Ke Zhou and Krisztian Balog. Their work appears in journals such as ACM Transactions on Information Systems, ACM SIGIR Forum, Digital Journalism, VUBIR (Vrije Universiteit Brussel) and UvA-DARE (University of Amsterdam).

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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