Robert J. Hilderman

24 papers receiving 258 citations

Peers

Robert J. Hilderman
Comparison fields: 5 of 47
  • Information Systems 203
  • Artificial Intelligence 154
  • Computational Theory and Mathematics 103
  • Signal Processing 101
  • Computer Networks and Communications 45
Replace Aaron Ceglar with:
Aaron Ceglar Australia
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Antonio Gomariz Spain
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Countries citing papers authored by Robert J. Hilderman

Since Specialization
Citations

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

Fields of papers citing papers by Robert J. Hilderman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert J. Hilderman. 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 Robert J. Hilderman. The network helps show where Robert J. Hilderman may publish in the future.

Co-authorship network of co-authors of Robert J. Hilderman

This figure shows the co-authorship network connecting the top 25 collaborators of Robert J. Hilderman. A scholar is included among the top collaborators of Robert J. Hilderman 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 Robert J. Hilderman. Robert J. Hilderman 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
#WorkIndexed citations
1 5
2 3
3
Knowledge Discovery and Interestingness Measures: A Survey
10
4
Categorical proportional difference: a feature selection method for text categorization
30
5
A characterization of wordnet features in Boolean models for text classification
12
6
Evaluating WordNet Features in Text Classification Models.
14
7
Assessing the Interestingness of Discovered Knowledge Using a Principled Objective Approach
4
8 4
9 9
10 1
11 1
12 0
13
Visualizing data mining results with domain generalization graphs
4
14 101
15
Ranking the Interestingness of Summaries from Data Mining Systems
9
16
Heuristic for Ranking the Interestigness of Discovered Knowledge
2
17 24
18 2
19
A Technique for Generalizing Temporal Durations in Relational Databases
1
20 17

About Robert J. Hilderman

Robert J. Hilderman is a scholar working on Signal Processing, Information Systems and Computer Networks and Communications, having authored 26 papers that have together received 286 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (14 papers), Data Management and Algorithms (10 papers) and Rough Sets and Fuzzy Logic (6 papers). The work is most often cited by research in Signal Processing (101 citations), Information Systems (203 citations) and Computational Theory and Mathematics (103 citations). Robert J. Hilderman has collaborated with scholars based in Canada. Frequent co-authors include Howard J. Hamilton, Nick Cercone, Garrett Nicolai, Liangchun Li, N. Cercone and Richard Dosselmann. Their work appears in journals such as IEEE Transactions on Software Engineering, Journal of Intelligent Information Systems and International Journal of Pattern Recognition and 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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