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Martin Hugh Goodfellow

dblp:73/7979 · DBLP profile ↗
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3ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0003-2151-8442ORCID · reported

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

Databases, data management, data science and information retrieval · 2Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021

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 · 91% Indexing and storage engines · 9%

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

TopicWeightPapersLastEvidence papers
Query processing and optimization › view maintenance
incremental view maintenance
0.212013
Algebraic incremental maintenance of XML views · ACM Trans. Database Syst. 2013
Query processing and optimization
view maintenance
0.212013
Algebraic incremental maintenance of XML views · ACM Trans. Database Syst. 2013
Query processing and optimization
XML query processing
0.212013
Algebraic incremental maintenance of XML views · ACM Trans. Database Syst. 2013

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

structural join algorithms · 0.2algebraic propagation · 0.2
YearPublicationVenuePosition
2023 Tips for Effective Blended Learning for Computer Science Education
abstract
Blended learning is the combination of in-person teaching and online activities. For example, combining face-to-face lectures/tutorials with online videos and assessments. With the adoption of non-traditional, not fully on-campus courses, such as degree and graduate apprenticeships in the UK, CPD, re/upskilling, and alternative teaching methods being required due to the pandemic, many different teaching strategies have been explored. Blended learning is one of these strategies and has proven popular for both universities and students.
Martin Hugh Goodfellow, Konstantinos Liaskos
ITiCSE (2)1
2013 Algebraic incremental maintenance of XML views
abstract
Materialized views can bring important performance benefits when querying XML documents. In the presence of XML document changes, materialized views need to be updated to faithfully reflect the changed document. In this work, we present an algebraic approach for propagating source updates to XML materialized views expressed in a powerful XML tree pattern formalism. Our approach differs from the state-of-the-art in the area in two important ways. First, it relies on set-oriented, algebraic operations, to be contrasted with node-based previous approaches. Second, it exploits state-of-the-art features of XML stores and XML query evaluation engines, notably XML structural identifiers and associated structural join algorithms. We present algorithms for determining how updates should be propagated to views, and highlight the benefits of our approach over existing algorithms through a series of experiments.
Angela Bonifati, Martin Hugh Goodfellow, Ioana Manolescu, Domenica Sileo
ACM Trans. Database Syst.2
2011 Algebraic incremental maintenance of XML views
abstract
Materialized views can bring important performance benefits when querying XML documents. In the presence of XML document changes, materialized views need to be updated to faithfully reflect the changed document. In this work, we present an algebraic approach for propagating source updates to XML materialized views expressed in a powerful XML tree pattern formalism. Our approach differs from the state of the art in the area in two important ways. First, it relies on set-oriented, algebraic operations, to be contrasted with node-based previous approaches. Second, it exploits state-of-the-art features of XML stores and XML query evaluation engines, notably XML structural identifiers and associated structural join algorithms. We present algorithms for determining how updates should be propagated to views, and highlight the benefits of our approach over existing algorithms through a series of experiments.
Angela Bonifati, Martin Hugh Goodfellow, Ioana Manolescu, Domenica Sileo
EDBT2