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

Richard G. Ramirez

dblp:53/971 · DBLP profile ↗
← Back
6ranked-venue papers
5as first author
0since 2021 · last 1997
—ORCID · none

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

Artificial intelligence and machine learning · 3 · 3 first-authorDatabases, data management, data science and information retrieval · 3 · 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.

Databases, data mining, and information retrieval
1 paper
Database system architecture and tuning · 50% Distributed and cloud data management · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed and cloud data management
consistency maintenance
0.011997
Independently Updated Views · IEEE Trans. Knowl. Data Eng. 1997
Database system architecture and tuning
view management
0.011997
Independently Updated Views · IEEE Trans. Knowl. Data Eng. 1997

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

timestamp-based resolution · 0.0differential table · 0.0
YearPublicationVenuePosition
1997 Independently Updated Views
abstract
Independently updated views (IUVs) are updated versions of a relational view. Unlike traditional views, updating an IUV changes only that IUV and not the underlying database. Updates to an IUV are stored in a differential table (DT) and incorporated when the IUV is accessed. There is no restriction on the type of query used to define the IUV. Applications of IUVs include alternative scenarios for decision support, local updating of distributed snapshots, and CAD versioning. IUVs allow versions to be defined on dynamic databases. This may cause inconsistencies because both the IUV and the base tables on which the IUV is defined can be updated independently of one another. We introduce "overlapping updates" that cause such inconsistencies and present algorithms for their detection and resolution using timestamps. These algorithms do not impose additional overhead on the database and require only the modification of the DT. A performance analysis indicates that the cost of querying IUVs is reasonable for a wide range of queries, views, and access strategies. We also consider a materialized implementation of IUVs. Materialized IUVs do not require a DT, relying instead on additional system columns for operation codes and timestamps. Results suggest a mix of implementation strategies for different types of IUV applications, depending on the frequency and nature of queries on the IUVs, the IUV sizes, and how actively the base tables are updated.
Uday R. Kulkarni, Richard G. Ramirez
IEEE Trans. Knowl. Data Eng.2
1996 Derived data for decision support systems
Richard G. Ramirez, Uday R. Kulkarni, Kathleen A. Moser
Decis. Support Syst.1
1993 Independence and mappings in model-based decision support systems
Richard G. Ramirez, Chee Ching, Robert D. St. Louis
Decis. Support Syst.1
1990 Representing generalizations and exceptions in expert database systems
Richard G. Ramirez, Ronald Dattero, Joobin Choobineh
Decis. Support Syst.1
1990 Using logic programming for formal specification and validation of data models
Richard G. Ramirez, Joobin Choobineh, Ronald Dattero
Inf. Manag.1
1990 Extension of relational views to derived relations with exceptions
Richard G. Ramirez, Ronald Dattero, Joobin Choobineh
Inf. Syst.1