Robert J. Hilderman

24 papers receiving 258 citations

Peers

Robert J. Hilderman
Comparison fields: 5 of 47
  • Signal Processing 101
  • Information Systems 203
  • Computational Theory and Mathematics 103
  • Artificial Intelligence 154
  • Computer Networks and Communications 45
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Aaron Ceglar Australia
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Ted Gueniche Canada
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-authors

The 6 scholars most cited alongside Robert J. Hilderman, 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 Robert J. Hilderman Line = papers co-authored together Robert J. Hilderman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001101
2
Categorical proportional difference: a feature selection method for text categorization
200830
3 199924
4 199817
5 200317
6
Evaluating WordNet Features in Text Classification Models.
200614
7
A characterization of wordnet features in Boolean models for text classification
200612
8
Knowledge Discovery and Interestingness Measures: A Survey
201210
9
Ranking the Interestingness of Summaries from Data Mining Systems
19999
10 20029
11 20096
12 20026
13 20165
14
Visualizing data mining results with domain generalization graphs
20014
15 20054
16
Assessing the Interestingness of Discovered Knowledge Using a Principled Objective Approach
20064
17 20163
18
Heuristic for Ranking the Interestigness of Discovered Knowledge
19992
19 19992
20 20152

About Robert J. Hilderman

Robert J. Hilderman is a scholar working on Information Systems, Signal Processing, Artificial Intelligence, Computer Networks and Communications and Computational Theory and Mathematics, 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), Rough Sets and Fuzzy Logic (6 papers), Advanced Database Systems and Queries (5 papers), Text and Document Classification Technologies (4 papers), Advanced Text Analysis Techniques (3 papers), Distributed systems and fault tolerance (3 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Signal Processing (101 citations), Information Systems (203 citations), Computational Theory and Mathematics (103 citations), Artificial Intelligence (154 citations) and Computer Networks and Communications (45 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, International Journal of Pattern Recognition and Artificial Intelligence, International Journal of Business Intelligence and Data Mining and Intelligent Data Analysis.

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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