Peter Mika

5.3k total citations
87 papers, 2.0k citations indexed

About

Peter Mika is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Peter Mika has authored 87 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Artificial Intelligence, 44 papers in Information Systems and 13 papers in Management Science and Operations Research. Recurrent topics in Peter Mika's work include Semantic Web and Ontologies (51 papers), Web Data Mining and Analysis (25 papers) and Data Quality and Management (13 papers). Peter Mika is often cited by papers focused on Semantic Web and Ontologies (51 papers), Web Data Mining and Analysis (25 papers) and Data Quality and Management (13 papers). Peter Mika collaborates with scholars based in Spain, United Kingdom and Netherlands. Peter Mika's co-authors include Hugo Zaragoza, Jeffrey Pound, Roi Blanco, Giovanni Tummarello, Steffen Staab, Jennifer Golbeck, Tim Finin, Pedro Domingos, Anupam Joshi and Robin R. Vallacher and has published in prestigious journals such as Scientometrics, Proceedings of the VLDB Endowment and Information Processing & Management.

In The Last Decade

Peter Mika

82 papers receiving 1.8k citations

Peers

Peter Mika
Comparison fields: 5 of 87
  • Artificial Intelligence 1.2k
  • Information Systems 1.0k
  • Computer Networks and Communications 390
  • Statistical and Nonlinear Physics 343
  • Management Science and Operations Research 270
Replace Alexandre Passant with:
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Sreenivas Gollapudi United States
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Alexandre Passant Ireland View profile →
Citations per field, relative to Peter Mika
Peter Mika · 1×
Citations per year, relative to Peter Mika
Peter Mika · 1×

Countries citing papers authored by Peter Mika

Since Specialization
Citations

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

Fields of papers citing papers by Peter Mika

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Mika

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Mika. A scholar is included among the top collaborators of Peter Mika based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peter Mika. Peter Mika is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1
Leveraging Wikipedia Knowledge for Entity Recommendations.
3
2
Proceedings of the 12th International Semantic Web Conference - Part II
4
3 17
4 7
5 4
6 10
7
Year of the Monkey: Lessons from the First Year of SearchMonkey.
0
8
Mining for Social Serendipity
5
9 6
10
Social Networks and the Semantic Web (Semantic Web and Beyond)
34
11
The Semantic Web, 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15
6
12 0
13
Let the Citizen Speak: A demand-driven e-government portal using Semantic Web Technology
1
14 5
15 14
16
Semantics-based publication management using RSS and FOAF
4
17 224
18 17
19 6
20
Foundations for DAML-S: Aligning DAML-S to DOLCE
1

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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