Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Assessing Acceptance of Assistive Social Agent Technology by Older Adults: the Almere Model
This map shows the geographic impact of Bob Wielinga'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 Bob Wielinga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bob Wielinga more than expected).
This network shows the impact of papers produced by Bob Wielinga. 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 Bob Wielinga. The network helps show where Bob Wielinga may publish in the future.
Co-authorship network of co-authors of Bob Wielinga
This figure shows the co-authorship network connecting the top 25 collaborators of Bob Wielinga.
A scholar is included among the top collaborators of Bob Wielinga 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 Bob Wielinga. Bob Wielinga 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
1.
Wielemaker, Jan, et al.. (2017). How Plausible is Automatic Annotation of Scientific Spreadsheets. 2065. 26–31.
2.
Wielinga, Bob, et al.. (2012). Designing a search and rescue simulation environment for studying the performance of agent organizations. VU Research Portal. 24. 115–122.1 indexed citations
3.
Boer, Victor de, et al.. (2006). Extracting Instances of Relations from Web Documents using Redundancy. Lecture notes in computer science. 4011. 245–258.9 indexed citations
4.
Hagen, Simen, et al.. (2005). Recommending Informative Links. UvA-DARE (University of Amsterdam).5 indexed citations
Fensel, Dieter, Enrico Motta, V. Richard Benjamins, et al.. (1999). The Unified Problem-Solving Method Development Language. Ecological Entomology.7 indexed citations
7.
Fensel, Dieter, V. Richard Benjamins, Enrico Motta, & Bob Wielinga. (1999). UPML: a framework for knowledge system reuse. UvA-DARE (University of Amsterdam). 16–21.51 indexed citations
8.
Benjamins, V. Richard, et al.. (1997). Making knowledge engineering technology work. UvA-DARE (University of Amsterdam). 56–61.4 indexed citations
9.
Schreiber, A.T., et al.. (1995). The KACTUS View on the 'O' word. UvA-DARE (University of Amsterdam). 159–168.55 indexed citations
10.
Schreiber, A.T., et al.. (1994). The CommonKADS conceptual modelling language. UvA-DARE (University of Amsterdam).2 indexed citations
11.
Schreiber, Guus, Bob Wielinga, & Joost Breuker. (1993). KADS : a principled approach to knowledge-based system development. Academic Press eBooks.187 indexed citations
Elshout, Jan J., et al.. (1982). PDP: a protocol diagnostic program for problem solving in physics. European Conference on Artificial Intelligence. 278–280.1 indexed citations
18.
Elshout, Jan J. & Bob Wielinga. (1979). A computational approach to the study of human skill acquisition. International Joint Conference on Artificial Intelligence. 244–246.1 indexed citations
19.
Bornat, Richard & Bob Wielinga. (1976). Does AI programming really have to be like knitting with spaghetti. 56–62.1 indexed citations
20.
Brady, J. Michael & Bob Wielinga. (1976). Seeing a pattern as a character. 63–73.3 indexed citations
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.