Nedim Lipka

1.3k citations
44 papers · 601 indexed · h-index 13
Topics
Topic Modeling (24 papers)Natural Language Processing Techniques (13 papers)Advanced Graph Neural Networks (8 papers)

In The Last Decade

Nedim Lipka

37 papers receiving 560 citations

Peers

Nedim Lipka
Comparison fields: 5 of 69
  • Artificial Intelligence 434
  • Information Systems 177
  • Communication 118
  • Computer Vision and Pattern Recognition 71
  • Statistical and Nonlinear Physics 56
Replace Thomas Gottron with:
Thomas Gottron Germany
Yiu‐Kai Ng United States
Dominik Kowald Austria
Tim Donkers Germany
Jinghua Piao China
Denis Kotkov Finland
Avishek Anand Germany
James Blustein Canada
Stefano Faralli Italy
Nedim Lipka relative to Thomas Gottron Germany Thomas Gottron's profile →
Citations per field
00.5×10×15.3×
Thomas Gottron · 1×
Citations per year

Countries citing papers authored by Nedim Lipka

Since Specialization
Citations

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

Fields of papers citing papers by Nedim Lipka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nedim Lipka

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 1
5 40
6 1
7
Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
6
8 126
9 14
10 1
11 2
12 8
13 21
14 1
15 9
16 2
17 91
18
Evaluating Cross-Language Explicit Semantic Analysis and Cross Querying at TEL@CLEF 2009
1
19 0
20 11

About Nedim Lipka

Nedim Lipka is a scholar working on Artificial Intelligence, Communication and Information Systems, having authored 44 papers that have together received 601 indexed citations. Recurring topics across this work include Topic Modeling (24 papers), Natural Language Processing Techniques (13 papers) and Advanced Graph Neural Networks (8 papers). The work is most often cited by research in Communication (118 citations), Artificial Intelligence (434 citations) and Information Systems (177 citations). Nedim Lipka has collaborated with scholars based in United States, Germany and South Korea. Frequent co-authors include Benno Stein, Ryan A. Rossi, Maik Anderka, Peter Prettenhofer, Anup Rao, Tung Mai, Nesreen K. Ahmed, Danai Koutra, Jiong Zhu and Sungchul Kim. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Language Resources and Evaluation and arXiv (Cornell University).

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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