Christoph Goller

993 total citations
12 papers, 466 citations indexed

About

Christoph Goller is a scholar working on Artificial Intelligence, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Christoph Goller has authored 12 papers receiving a total of 466 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 5 papers in Molecular Biology and 2 papers in Computational Theory and Mathematics. Recurrent topics in Christoph Goller's work include Neural Networks and Applications (4 papers), Biomedical Text Mining and Ontologies (4 papers) and Semantic Web and Ontologies (4 papers). Christoph Goller is often cited by papers focused on Neural Networks and Applications (4 papers), Biomedical Text Mining and Ontologies (4 papers) and Semantic Web and Ontologies (4 papers). Christoph Goller collaborates with scholars based in Germany and Italy. Christoph Goller's co-authors include Andreas Küchler, Reinhold Letz, Joachim P. Steinbach, Johann Schumann, Alessandro Sperduti, Antonina Starita, Marco Gori, M. O. Schurr, Jörg Denzinger and Marco Maggini and has published in prestigious journals such as Journal of Automated Reasoning, Journal of Biomedical Semantics and Use Siena air (University of Siena).

In The Last Decade

Christoph Goller

12 papers receiving 427 citations

Peers

Christoph Goller
E. K. Tang Singapore
Shenkai Gu United Kingdom
Jan Lemeire Belgium
Ray Reiter Canada
Kai Ye China
Cheng Ji China
Christoph Goller
Citations per year, relative to Christoph Goller Christoph Goller (= 1×) peers Takashi Chikayama

Countries citing papers authored by Christoph Goller

Since Specialization
Citations

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

Fields of papers citing papers by Christoph Goller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christoph Goller. 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 Christoph Goller. The network helps show where Christoph Goller may publish in the future.

Co-authorship network of co-authors of Christoph Goller

This figure shows the co-authorship network connecting the top 25 collaborators of Christoph Goller. A scholar is included among the top collaborators of Christoph Goller 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 Christoph Goller. Christoph Goller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Schurr, M. O., Christoph Goller, Robin Seidel, et al.. (2019). Ontology-based specification and generation of search queries for post-market surveillance. Journal of Biomedical Semantics. 10(1). 9–9. 5 indexed citations
2.
Schurr, M. O., M. Leenen, Heinrich Herre, et al.. (2018). Ontology-based search for risk-relevant PMS data. p 232. 1–4. 3 indexed citations
3.
Schurr, M. O., Christoph Goller, Robin Seidel, et al.. (2017). Search Ontology Generator (SONG): Ontology-Based Specification and Generation of Search Queries.. 1 indexed citations
4.
Goller, Christoph, et al.. (2014). Search ontology, a new approach towards semantic search. GI-Jahrestagung. 667–672. 5 indexed citations
5.
Goller, Christoph, Marco Gori, & Marco Maggini. (2003). Feature extraction from data structures with unsupervised recursive neural networks. Use Siena air (University of Siena). 2. 1121–1126. 4 indexed citations
6.
Goller, Christoph & Andreas Küchler. (2002). Learning task-dependent distributed representations by backpropagation through structure. Proceedings of International Conference on Neural Networks (ICNN'96). 1. 347–352. 333 indexed citations
7.
Goller, Christoph. (1999). Learning search-control heuristics for automated deduction systems with folding architecture networks.. The European Symposium on Artificial Neural Networks. 45–50. 3 indexed citations
8.
Denzinger, Jörg, Matthias Fuchs, Christoph Goller, & Stephan Schulz. (1999). Learning from Previous Proof Experience: A Survey. Publication Server of Kaiserslautern University of Technology (Kaiserslautern University of Technology). 5 indexed citations
9.
Sperduti, Alessandro, Antonina Starita, & Christoph Goller. (1997). Distributed representations for terms in hybrid reasoning systems. Research Padua Archive (University of Padua). 329–344. 2 indexed citations
10.
Letz, Reinhold, et al.. (1997). SETHEO and E-SETHEO - The CADE-13 Systems. Journal of Automated Reasoning. 18(2). 237–246. 41 indexed citations
11.
Sperduti, Alessandro, Antonina Starita, & Christoph Goller. (1995). Learning distributed representations for the classification of terms. International Joint Conference on Artificial Intelligence. 347. 509–515. 14 indexed citations
12.
Letz, Reinhold, et al.. (1994). Controlled integration of the cut rule into connection tableau calculi. Journal of Automated Reasoning. 13(3). 297–337. 50 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.

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