Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Shaoyu Zhou

dblp:98/6245 · DBLP profile ↗
← Back
2ranked-venue papers
1as first author
0since 2021 · last 1998
—ORCID · unresolved

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

Systems, architecture and hardware · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1

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.

Databases, data mining, and information retrieval
1 paper
Query processing and optimization · 87% Database system architecture and tuning · 13%

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

TopicWeightPapersLastEvidence papers
Query processing and optimization › selectivity estimation
learned selectivity estimation
0.011998
Selectivity Estimation in Extensible Databases - A Neural Network Approach · VLDB 1998
Query processing and optimization
selectivity estimation
0.011998
Selectivity Estimation in Extensible Databases - A Neural Network Approach · VLDB 1998
Database system architecture and tuning
extensible database system
0.011998
Selectivity Estimation in Extensible Databases - A Neural Network Approach · VLDB 1998

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

neural network · 0.0
YearPublicationVenuePosition
1998 Selectivity Estimation in Extensible Databases - A Neural Network Approach
M. Seetha Lakshmi, Shaoyu Zhou
VLDB2
1997 Cache Modeling in a Performance Evaluator for Parallel Database Systems
abstract
Cache modelling is an important issue in developing an analytical performance evaluator to estimate the performance of applications running on parallel DBMSs. This paper describes a cache model developed for parallel cache management in the Oracle7 parallel server. Some preliminary results have also been obtained by using the cache model to predict the cache hit ratio for varying database sizes and varying numbers of participating processing elements.
Shaoyu Zhou, Neven Tomov, M. Howard Williams, Albert G. Burger, Hamish Taylor
MASCOTS1