Hans Chalupsky

859 citations
24 papers · 443 · h-index 9

Impact in

Papers in

Hans Chalupsky

22 papers receiving 357 citations

Peers

Hans Chalupsky
Comparison fields: 5 of 52
  • Artificial Intelligence 301
  • Computer Networks and Communications 179
  • Information Systems 162
  • Information Systems and Management 43
  • Statistical and Nonlinear Physics 44
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Citations per year

Countries citing papers authored by Hans Chalupsky

Since Specialization
Citations

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

Fields of papers citing papers by Hans Chalupsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
OntoMorph: A Translation System for Symbolic Knowledge.
2000114
2
Electric Elves: Applying Agent Technology to Support Human Organizations
200181
3
An Overview of KQML: A Knowledge Query and Manipulation Language
199248
4 200448
5 200538
6 200827
7 200220
8 200314
9
Electric Elves: Immersing an Agent Organization in a Human Organization
200011
10
Learning by Reading: Two Experiments
20068
11 19937
12 20036
13 20065
14
Reasoning about Incomplete Agents
20005
15 20043
16
Simba: belief ascription by way of simulative reasoning
19962
17
Story-Level Inference and Gap Filling to Improve Machine Reading
20121
18
DataFinder: Using Ontologies and Reasoning to Enhance Metadata Search
20051
19
"Its All Made Up" — Why We Should Stop Building Representations Based on Interpretive Models and Focus on Experimental Evidence Instead
20141
20 19931

About Hans Chalupsky

Hans Chalupsky is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Statistical and Nonlinear Physics and Information Systems and Management, having authored 24 papers that have together received 443 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (8 papers), Logic, Reasoning, and Knowledge (5 papers), Natural Language Processing Techniques (4 papers), AI-based Problem Solving and Planning (4 papers), Multi-Agent Systems and Negotiation (4 papers), Topic Modeling (3 papers), Scientific Computing and Data Management (3 papers) and Complex Network Analysis Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (301 citations), Computer Networks and Communications (179 citations), Information Systems (162 citations), Information Systems and Management (43 citations) and Statistical and Nonlinear Physics (44 citations). Hans Chalupsky has collaborated with scholars based in United States, Slovenia and Taiwan. Frequent co-authors include Shou-De Lin, Thomas A. Russ, Yolanda Gil, David V. Pynadath, Kristina Lerman, Craig A. Knoblock, Jean Oh, Milind Tambe, Richard Fritzson and Tim Finin. Their work appears in journals such as Semantic Web, The Knowledge Engineering Review, ACM SIGMOD Record, IEEE Transactions on Knowledge and Data Engineering and Journal of Experimental & Theoretical 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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