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Felix I. Wyss

dblp:77/4394 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

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

Artificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1Graphics, computer vision, multimedia, augmented reality and games · 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 · 50% Data integration and cleaning · 25% Data models and query languages · 25%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization › query optimization
distributed query optimization
0.112007
Extending relational query optimization to dynamic schemas for information integration in multidatabases · SIGMOD Conference 2007
Data integration and cleaning › database integration
multidatabase integration
0.112007
Extending relational query optimization to dynamic schemas for information integration in multidatabases · SIGMOD Conference 2007
Query processing and optimization
query optimization
0.112007
Extending relational query optimization to dynamic schemas for information integration in multidatabases · SIGMOD Conference 2007

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

query pushing · 0.1bi-level optimization · 0.1
YearPublicationVenuePosition
2016 Generation and Pruning of Pronunciation Variants to Improve ASR Accuracy
Zhenhao Ge, Aravind Ganapathiraju, Ananth N. Iyer, Scott A. Randal, Felix I. Wyss
INTERSPEECH5
2007 Extending relational query optimization to dynamic schemas for information integration in multidatabases
abstract
This paper extends relational processing and optimization to the FISQL/FIRA languages for dynamic schema queries over multidatabases. Dynamic schema queries involve the creation and restructuring of metadata at runtime. We present a full implementation of a FISQL/FIRA engine, which includes subqueries and all transformational capabilities of FISQL/FIRA on distributed, multidatabase platforms. An important application of the system is to enhance traditional information architectures by enabling the creation and maintenance of dynamic wrappers and mapping queries at source databases within GAV, LAV, GLAV, peer-to-peer, or other integration frameworks. In addition to fully supporting FISQL/FIRA on multidatabases, our implementation introduces a bi-level optimization paradigm where purely relational sub-fragments of queries are pushed into source engines. This paradigm shares features of canonical distributed database processing, but has a new dimension through the extension of the relational model to dynamic schemas. We present empirical results showing the feasibility of optimization in this context, and discuss tradeoffs involved. Our system is the first to extend relational databases with these capabilities on this scale.
Catharine M. Wyss, Felix I. Wyss
SIGMOD Conference2