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Eyal Dushkin

dblp:219/9702 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 2 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
Algorithms and data structures · 50% Combinatorics and discrete mathematics · 50%
Databases, data mining, and information retrieval
1 paper
Data mining · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Combinatorics and discrete mathematics
partial orders
0.312018
Top-k Sorting Under Partial Order Information · SIGMOD Conference 2018
Algorithms and data structures › sequence algorithms
sorting
0.312018
Top-k Sorting Under Partial Order Information · SIGMOD Conference 2018
Data mining
crowdsourcing
0.112018
Top-k Sorting Under Partial Order Information · SIGMOD Conference 2018

Methods — techniques the papers use, named apart from their topics

comparison-based sorting · 0.7
YearPublicationVenuePosition
2019 Query Driven Data Labeling with Experts: Why Pay Twice?
Eyal Dushkin, Shay Gershtein, Tova Milo, Slava Novgorodov
EDBT1
2018 Top-k Sorting Under Partial Order Information
abstract
We address the problem of sorting the top-k elements of a set, given a predefined partial order over the set elements. Our means to obtain missing order information is via a comparison operator that interacts with a crowd of domain experts to determine the order between two unordered items. The practical motivation for studying this problem is the common scenario where elements cannot be easily compared by machines and thus human experts are harnessed for this task. As some initial partial order is given, our goal is to optimally exploit it in order to minimize the domain experts work.
Eyal Dushkin, Tova Milo
SIGMOD Conference1