Hans Chalupsky

854 citations
24 papers · 444 indexed · h-index 9

Impact in

Papers in

    • Semantic Web and Ontologies 8
    • Logic, Reasoning, and Knowledge 5
    • Multi-Agent Systems and Negotiation 4
    • AI-based Problem Solving and Planning 4
    • Natural Language Processing Techniques 4
    • Topic Modeling 3
    • Scientific Computing and Data Management 3

Hans Chalupsky

22 papers receiving 358 citations

Peers

Hans Chalupsky
Comparison fields: 5 of 52
  • Artificial Intelligence 306
  • Computer Networks and Communications 179
  • Information Systems 162
  • Information Systems and Management 45
  • 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-authorship network

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
#Work
1 20240
2
"Its All Made Up" — Why We Should Stop Building Representations Based on Interpretive Models and Focus on Experimental Evidence Instead
20141
3
Story-Level Inference and Gap Filling to Improve Machine Reading
20121
4 20070
5
Modeling, searching, and explaining abnormal instances in multi-relational networks
20061
6
Learning by Reading: Two Experiments
20068
7 20065
8
DataFinder: Using Ontologies and Reasoning to Enhance Metadata Search
20051
9 200538
10 200448
11 20036
12
Tools for Assembling and Managing Scalable Knowledge Bases
20031
13 200220
14
Electric Elves: Applying Agent Technology to Support Human Organizations
200181
15
OntoMorph: A Translation System for Symbolic Knowledge.
2000115
16
Reasoning about Incomplete Agents
20005
17
Electric Elves: Immersing an Agent Organization in a Human Organization
200011
18
Simba: belief ascription by way of simulative reasoning
19962
19 19937
20
An Overview of KQML: A Knowledge Query and Manipulation Language
199248

About Hans Chalupsky

Hans Chalupsky is a scholar working on Artificial Intelligence, Information Systems and Management, Software, Computer Networks and Communications and Statistical and Nonlinear Physics, having authored 24 papers that have together received 444 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (8 papers), Logic, Reasoning, and Knowledge (5 papers), Multi-Agent Systems and Negotiation (4 papers), AI-based Problem Solving and Planning (4 papers), Natural Language Processing Techniques (4 papers), Topic Modeling (3 papers), Complex Network Analysis Techniques (3 papers) and Scientific Computing and Data Management (3 papers). The work is most often cited by research in Artificial Intelligence (306 citations), Computer Networks and Communications (179 citations), Information Systems (162 citations), Information Systems and Management (45 citations) and Statistical and Nonlinear Physics (44 citations). Hans Chalupsky has collaborated with scholars based in United States, Canada and Slovenia. Frequent co-authors include Shou-De Lin, Thomas A. Russ, Yolanda Gil, Kristina Lerman, Milind Tambe, David V. Pynadath, Jean Oh, Craig A. Knoblock, Stewart Shapiro and Tim Finin. Their work appears in journals such as The Knowledge Engineering Review, ACM SIGMOD Record, IEEE Transactions on Knowledge and Data Engineering, Semantic Web 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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