Mario Lenz

1.1k citations
12 papers · 214 · h-index 7

Impact in

    • AI-based Problem Solving and Planning
    • Semantic Web and Ontologies
    • Multi-Agent Systems and Negotiation
    • Logic, Reasoning, and Knowledge
    • Topic Modeling

Papers in

Mario Lenz

11 papers receiving 191 citations

Peers

Mario Lenz
Comparison fields: 5 of 60
  • Artificial Intelligence 137
  • Software 8
  • Information Systems 42
  • Management Information Systems 11
  • Computational Theory and Mathematics 15
Replace Tomoyuki Aotani with:
Tomoyuki Aotani Japan
Ioanna Lytra Austria
Kenichi Taniguchi Japan
Parita Jain India
Rui Jiang China
Peter McBrien United Kingdom
Maciej Szreter Poland
Philipp Hanschke Germany
Mario Lenz relative to Tomoyuki Aotani Japan Tomoyuki Aotani's profile →
Citations per field
00.5×3.7×
Tomoyuki Aotani · 1×
Citations per year

Countries citing papers authored by Mario Lenz

Since Specialization
Citations

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

Fields of papers citing papers by Mario Lenz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Mario Lenz, 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 Mario Lenz Line = papers co-authored together Mario Lenz links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 199874
2
Case-Based Reasoning Technology, From Foundations to Applications
199849
3 201628
4
Textual CBR
199822
5
CBR for Dynamic Situation Assessment in an Agent-Oriented Setting
199814
6 20139
7 19966
8 19984
9
Managing the Knowledge Contained in Technical Documents.
19984
10
The SIMATIC Knowledge Manager
19993
11 20131
12
Lazy Propagation in Case Retrieval Nets.
19960

About Mario Lenz

Mario Lenz is a scholar working on Artificial Intelligence, Organic Chemistry, Computer Networks and Communications, Molecular Biology and Information Systems, having authored 12 papers that have together received 214 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (4 papers), AI-based Problem Solving and Planning (2 papers), Pharmacogenetics and Drug Metabolism (1 paper), Estrogen and related hormone effects (1 paper), Web Data Mining and Analysis (1 paper), Advanced Database Systems and Queries (1 paper), Logic, Reasoning, and Knowledge (1 paper) and Rough Sets and Fuzzy Logic (1 paper). The work is most often cited by research in Artificial Intelligence (137 citations), Software (8 citations), Information Systems (42 citations), Management Information Systems (11 citations) and Computational Theory and Mathematics (15 citations). Mario Lenz has collaborated with scholars based in Germany, Switzerland and China. Frequent co-authors include Stefan Weß, Hans-Dieter Burkhard, Mirjam Kunze, Johannes D. Aebi, Rainer E. Martin, Bernd Kuhn, Robert Britton, Johannes Lehmann, Kurt E. Amrein and Hans Peter Märki. Their work appears in journals such as Organic & Biomolecular Chemistry, Tetrahedron Letters, AI Communications, Lecture notes in computer science and European Conference on Artificial Intelligence.

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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