Gemma C. Garriga

1.3k total citations · 1 hit paper
17 papers, 832 citations indexed

About

Gemma C. Garriga is a scholar working on Information Systems, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Gemma C. Garriga has authored 17 papers receiving a total of 832 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Information Systems, 9 papers in Computational Theory and Mathematics and 6 papers in Artificial Intelligence. Recurrent topics in Gemma C. Garriga's work include Data Mining Algorithms and Applications (10 papers), Rough Sets and Fuzzy Logic (7 papers) and Data Management and Algorithms (5 papers). Gemma C. Garriga is often cited by papers focused on Data Mining Algorithms and Applications (10 papers), Rough Sets and Fuzzy Logic (7 papers) and Data Management and Algorithms (5 papers). Gemma C. Garriga collaborates with scholars based in Finland, France and Germany. Gemma C. Garriga's co-authors include Markus Ojala, Kai Puolamäki, Sami Hanhijärvi, Heikki Mannila, Petra Kralj, Nada Lavrač, Roni Khardon, Luc De Raedt, Thomas Gärtner and Aristides Gionis and has published in prestigious journals such as Machine Learning, Journal of Machine Learning Research and Theoretical Computer Science.

In The Last Decade

Gemma C. Garriga

16 papers receiving 804 citations

Hit Papers

align trajectories

What are hit papers?

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.

Permutation Tests for Studying Classifier Performance

2009 413 citations Markus Ojala, Gemma C. Garriga profile →

Peers

Countries citing papers authored by Gemma C. Garriga

Since Specialization

Citations

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

Fields of papers citing papers by Gemma C. Garriga

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gemma C. Garriga. 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 Gemma C. Garriga. The network helps show where Gemma C. Garriga may publish in the future.

Co-authorship network of co-authors of Gemma C. Garriga

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

All Works

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17 of 17 papers shown

#	Work	Indexed citations
1	Machine Learning and Knowledge Discovery in Databases 2016 ·Lecture notes in computer science ·(unknown), (unknown), (unknown), Gemma C. Garriga, (unknown)	14
2	Formal Methods for Mining Structured Objects 2013 ·Studies in computational intelligence ·Gemma C. Garriga	0
3	Mining closed patterns in relational, graph and network data 2012 ·Annals of Mathematics and Artificial Intelligence ·Gemma C. Garriga, Roni Khardon, Luc De Raedt	3
4	Permutation Tests for Studying Classifier Performance 2010 ·Journal of Machine Learning Research ·Markus Ojala, Gemma C. Garriga	249
5	Banded structure in binary matrices 2010 ·Knowledge and Information Systems ·Gemma C. Garriga, (unknown), Heikki Mannila	11
6	Evaluating Query Result Significance in Databases via Randomizations 2010 ·Markus Ojala, Gemma C. Garriga, Aristides Gionis, Heikki Mannila	13
7	Permutation Tests for Studying Classifier Performance breakdown → 2009 ·Markus Ojala, Gemma C. Garriga	413
8	Guest editors’ introduction: special issue on mining and learning with graphs 2009 ·Machine Learning ·Thomas Gärtner, Gemma C. Garriga	5
9	Randomization Techniques for Graphs 2009 ·Sami Hanhijärvi, Gemma C. Garriga, Kai Puolamäki	40
10	Closed Sets for Labeled Data 2008 ·Journal of Machine Learning Research ·Gemma C. Garriga, Petra Kralj, Nada Lavrač	27
11	Banded structure in binary matrices 2008 ·Gemma C. Garriga, (unknown), Heikki Mannila	9
12	An approximation ratio for biclustering 2008 ·Information Processing Letters ·Kai Puolamäki, Sami Hanhijärvi, Gemma C. Garriga	7
13	On mining closed sets in multi-relational data 2007 ·International Joint Conference on Artificial Intelligence ·Gemma C. Garriga, Roni Khardon, Luc De Raedt	14
14	Cross-Mining Binary and Numerical Attributes 2007 ·Gemma C. Garriga, (unknown), Jouni K. Seppänen	6
15	A Linear Programming Approach for Molecular QSAR analysis 2006 ·Max Planck Institute for Plasma Physics ·Hiroto Saigo, Tadashi Kadowaki, Koji Tsuda, (unknown), Gemma C. Garriga, Thorsten Meinl	11
16	Horn axiomatizations for sequential data 2006 ·Theoretical Computer Science ·José L. Balcázar, Gemma C. Garriga	5
17	Frequent sets, sequences and taxonomies: new efficient algorithmic proposals 2000 ·(unknown), Gemma C. Garriga, (unknown)	5

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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