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.
On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems
This map shows the geographic impact of Viggo Kann'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 Viggo Kann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Viggo Kann more than expected).
This network shows the impact of papers produced by Viggo Kann. 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 Viggo Kann. The network helps show where Viggo Kann may publish in the future.
Co-authorship network of co-authors of Viggo Kann
This figure shows the co-authorship network connecting the top 25 collaborators of Viggo Kann.
A scholar is included among the top collaborators of Viggo Kann 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 Viggo Kann. Viggo Kann is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kann, Viggo, et al.. (2010). Constructing a Swedish General Purpose Polarity Lexicon : Random Walks in the People's Dictionary of Synonyms. 19–20.4 indexed citations
5.
Kann, Viggo, et al.. (2010). Global Evaluation of Random Indexing through Swedish Word Clustering Compared to the People’s Dictionary of Synonyms.1 indexed citations
Hassel, Martin, et al.. (2009). Global Evaluation of Random Indexing through Swedish Word Clustering Compared to the People’s Dictionary of Synonyms. Recent Advances in Natural Language Processing. 376–380.4 indexed citations
8.
Sjöbergh, Jonas & Viggo Kann. (2006). Vad kan statistik avslöja om svenska sammansättningar. 199–214.1 indexed citations
9.
Kann, Viggo, et al.. (2004). Grammar checking for Swedish second language learners. 33–47.14 indexed citations
10.
Kann, Viggo, et al.. (2004). The development and performance of a grammar checker for Swedish : A language engineering perspective. Natural Language Engineering. 1(1).5 indexed citations
11.
Sjöbergh, Jonas & Viggo Kann. (2004). Finding the Correct Interpretation of Swedish Compounds, a Statistical Approach. Language Resources and Evaluation.21 indexed citations
12.
Kann, Viggo. (2004). Folkets användning av Lexin - en resurs.2 indexed citations
13.
Knutsson, Ola, et al.. (2000). Granska - an efficient hybrid system for Swedish grammar checking. DSpace repository (University of Tartu).35 indexed citations
Crescenzi, Pierluigi, et al.. (1999). Structure in Approximation Classes. IRIS Research product catalog (Sapienza University of Rome).37 indexed citations
16.
Amaldi, E. & Viggo Kann. (1998). On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems. Theoretical Computer Science. 209(1-2). 237–260.511 indexed citations breakdown →
17.
Kann, Viggo, Sanjeev Khanna, Jens Lagergren, & Alessandro Panconesi. (1997). On the Hardness of Approximating Max k-Cut and Its Dual. 1997. 61–67.44 indexed citations
Kann, Viggo. (1994). Polynomially bounded minimization problems that are hard to approximate. Nordic journal of computing. 1(3). 317–331.32 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.