Alex G. Büchner
- Information Systems top 2%
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Sociology and Political Science
- Signal Processing top 10%
- Co-authors
- Maurice MulvennaSarabjot Singh AnandJohn G. HughesWerner DubitzkyDavid BellMatthias Baumgarten
- Topics
- Data Mining Algorithms and Applications (5 papers)Data Management and Algorithms (4 papers)Rough Sets and Fuzzy Logic (2 papers)
- Partner nations
- United Kingdom
In The Last Decade
Alex G. Büchner
9 papers receiving 404 citations
Peers
Comparison fields: 5 of 61
- Information Systems 317
- Artificial Intelligence 115
- Computer Networks and Communications 111
- Sociology and Political Science 100
- Signal Processing 79
Countries citing papers authored by Alex G. Büchner
This map shows the geographic impact of Alex G. Büchner'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 Alex G. Büchner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alex G. Büchner more than expected).
Fields of papers citing papers by Alex G. Büchner
This network shows the impact of papers produced by Alex G. Büchner. 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 Alex G. Büchner. The network helps show where Alex G. Büchner may publish in the future.
Co-authorship network of co-authors of Alex G. Büchner
This figure shows the co-authorship network connecting the top 25 collaborators of Alex G. Büchner. A scholar is included among the top collaborators of Alex G. Büchner 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 Alex G. Büchner. Alex G. Büchner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Moodle Administration: An administrator's guide to configuring, securing, customizing, and extending Moodle | 4 |
| 2 | Context Mediation among Knowledge Discovery Components | 0 |
| 3 | Tree Growth Based Episode Mining without Candidate Generation. | 2 |
| 4 | Tree-Growth based Sequential and Associative Pattern Discovery. | 0 |
| 5 | Gaining insights into web customers using Web Intelligence | 1 |
| 6 | 232 | |
| 7 | Contextual Domain Knowledge for Incorporation in Data Mining Systems | 2 |
| 8 | 11 | |
| 9 | 158 | |
| 10 | Decision support using data mining | 57 |
| 11 | 19 |
About Alex G. Büchner
Alex G. Büchner is a scholar working on Signal Processing, Information Systems and Computer Networks and Communications, having authored 11 papers that have together received 486 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (5 papers), Data Management and Algorithms (4 papers) and Rough Sets and Fuzzy Logic (2 papers). The work is most often cited by research in Information Systems (317 citations), Information Systems and Management (55 citations) and Marketing (68 citations). Alex G. Büchner has collaborated with scholars based in United Kingdom. Frequent co-authors include Maurice Mulvenna, Sarabjot Singh Anand, John G. Hughes, Werner Dubitzky, David Bell and Matthias Baumgarten. Their work appears in journals such as Communications of the ACM, ACM SIGMOD Record and Data & Knowledge Engineering.
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.