D-Index & Metrics Best Publications

Stratos Idreos

Harvard University
United States

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 33 Citations 4,227 111 World Ranking 8765 National Ranking 4037

Overview

What is he best known for?

The fields of study he is best known for:

Database
Artificial intelligence
Computer network

Stratos Idreos focuses on Data mining, Database, Workload, Column and Context. His Data mining research is multidisciplinary, incorporating perspectives in Overhead, Information retrieval and Index. His research in Overhead focuses on subjects like Column, which are connected to Data access.

While the research belongs to areas of Index, he spends his time largely on the problem of Search engine indexing, intersecting his research to questions surrounding Metadata. His Database research integrates issues from Matching, Raw data and Parsing. His research investigates the link between Column and topics such as Analytics that cross with problems in Data management.

His most cited work include:

MonetDB: Two Decades of Research in Column-oriented Database Architectures (228 citations)
Overview of Data Exploration Techniques (158 citations)
Self-organizing tuple reconstruction in column-stores (142 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Database, Data mining, Distributed computing, Data structure and Search engine indexing. His study in Database is interdisciplinary in nature, drawing from both Overhead, Raw data and Memory bandwidth. Data mining is frequently linked to Data set in his study.

His work investigates the relationship between Distributed computing and topics such as Overlay network that intersect with problems in Download. His biological study spans a wide range of topics, including Query language, Metadata and Index. His View study combines topics in areas such as Query expansion and Data management.

He most often published in these fields:

Database (20.54%)
Data mining (16.96%)
Distributed computing (16.07%)

What were the highlights of his more recent work (between 2018-2021)?

Data structure (11.61%)
Distributed computing (16.07%)
Filter (1.79%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Data structure, Distributed computing, Filter, Information retrieval and Bloom filter. The Distributed computing study combines topics in areas such as Inference engine and Associative array. His work on Adaptive indexing as part of general Information retrieval research is often related to Point, thus linking different fields of science.

In most of his Bloom filter studies, his work intersects topics such as Scalability. Stratos Idreos performs integrative study on Scalability and Workload in his works. His NoSQL study incorporates themes from Query optimization, Open research and Data science.

Between 2018 and 2021, his most popular works were:

The Seattle Report on Database Research (20 citations)
The Log-Structured Merge-Bush & the Wacky Continuum (18 citations)
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn. (18 citations)

In his most recent research, the most cited papers focused on:

Database
Artificial intelligence
Computer network

The scientist’s investigation covers issues in Workload, Database research, Library science, Industrial engineering and Key. Workload overlaps with fields such as Data structure, Bloom filter, Binary logarithm, Scalability and Optimization problem in his research. A majority of his Industrial engineering research is a blend of other scientific areas, such as Path and Value.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

MonetDB: Two Decades of Research in Column-oriented Database Architectures

Stratos Idreos;Fabian Groffen;Niels Nes;Stefan Manegold.
IEEE Data(base) Engineering Bulletin (2012)

412 Citations

Overview of Data Exploration Techniques

Stratos Idreos;Olga Papaemmanouil;Surajit Chaudhuri.
international conference on management of data (2015)

261 Citations

NoDB: efficient query execution on raw data files

Ioannis Alagiannis;Renata Borovica;Miguel Branco;Stratos Idreos.
international conference on management of data (2012)

252 Citations

Self-organizing tuple reconstruction in column-stores

Stratos Idreos;Martin L. Kersten;Stefan Manegold.
international conference on management of data (2009)

216 Citations

Monkey: Optimal Navigable Key-Value Store

Niv Dayan;Manos Athanassoulis;Stratos Idreos.
international conference on management of data (2017)

165 Citations

H2O: a hands-free adaptive store

Ioannis Alagiannis;Stratos Idreos;Anastasia Ailamaki.
international conference on management of data (2014)

163 Citations

Merging what's cracked, cracking what's merged: adaptive indexing in main-memory column-stores

Stratos Idreos;Stefan Manegold;Harumi Kuno;Goetz Graefe.
very large data bases (2011)

161 Citations

The researcher's guide to the data deluge: querying a scientific database in just a few seconds

Martin L. Kersten;Stratos Idreos;Stefan Manegold;Erietta Liarou.
very large data bases (2011)

125 Citations

Here are my Data Files. Here are my Queries. Where are my Results

Stratos Idreos;Ioannis Alagiannis;Ryan Johnson;Anastasia Ailamaki.
conference on innovative data systems research (2011)

113 Citations

Dostoevsky: Better Space-Time Trade-Offs for LSM-Tree Based Key-Value Stores via Adaptive Removal of Superfluous Merging

Niv Dayan;Stratos Idreos.
international conference on management of data (2018)