Demo Data from EDBT 2026 / reviewers in the wild / expert
Tal Shinkar
dblp:238/0024
· DBLP profile ↗
2ranked-venue papers
2as first author
1since 2021 · last 2022
0000-0002-2590-5821ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
1 paper |
Coding theory · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › error-correcting codes › burst error correction
cluster-correcting codes |
0.6 | 1 | 2022 | Clustering-Correcting Codes · IEEE Trans. Inf. Theory 2022 |
Coding theory
error-correcting codes |
0.6 | 1 | 2022 | Clustering-Correcting Codes · IEEE Trans. Inf. Theory 2022 |
Coding theory › error-correcting codes › storage coding
DNA storage |
0.2 | 1 | 2022 | Clustering-Correcting Codes · IEEE Trans. Inf. Theory 2022 |
Methods — techniques the papers use, named apart from their topics
code construction · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Clustering-Correcting Codes
Tal Shinkar, Eitan Yaakobi, Andreas Lenz 0001, Antonia Wachter-Zeh |
IEEE Trans. Inf. Theory | 1 |
| 2019 | Clustering-Correcting CodesabstractA new family of codes, calledclustering-correcting codes, is presented in this paper. This family of codes is motivated by the special structure of the data that is stored in DNA-based storage systems. The data stored in these systems has the form of unordered sequences, also calledstrands, and every strand is synthesized thousands to millions of times, where some of these copies are read back during sequencing. Due to the unordered structure of the strands, an important task in the decoding process is to place them in their correct order. This is usually accomplished by allocating part of the strand for an index. However, in the presence of errors in the index field, important information on the order of the strands may be lost. Clustering-correcting codes ensure that if the distance between the index fields of two strands is small, their data fields have large distance. It is shown how this property enables to place the strands together in their correct clusters even in the presence of errors. We present lower and upper bounds on the size of clustering-correcting codes and an explicit construction of these codes which uses only a single symbol of redundancy. The results are first presented for the Hamming metric and are then extended for the edit distance. Tal Shinkar, Eitan Yaakobi, Andreas Lenz 0001, Antonia Wachter-Zeh |
ISIT | 1 |