Demo Data from EDBT 2026 / reviewers in the wild / expert
Lila Shnaiderman
dblp:62/156
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 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 |
Query processing and optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Query processing and optimization › XML query processing
twig pattern matching |
0.2 | 1 | 2015 | Multi-Core Processing of XML Twig Patterns · IEEE Trans. Knowl. Data Eng. 2015 |
Query processing and optimization
XML query processing |
0.2 | 1 | 2015 | Multi-Core Processing of XML Twig Patterns · IEEE Trans. Knowl. Data Eng. 2015 |
Parallel and multicore computing
parallel query processing |
0.1 | 1 | 2015 | Multi-Core Processing of XML Twig Patterns · IEEE Trans. Knowl. Data Eng. 2015 |
Methods — techniques the papers use, named apart from their topics
twigstack · 0.4pathstack · 0.4multi-threaded parallelization · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Multi-Core Processing of XML Twig PatternsabstractXML is based on a tree-structured data model. Naturally, the most popular XML querying language (XPath) uses patterns of selection predicates, on multiple elements related by a tree structure, which often may be abstracted by twig patterns. Finding all occurrences of such a twig pattern in an XML database is a basic operation for XML query processing. We present the parallel path stack algorithm (PPS) and the parallel twig stack algorithm (PTS). PPS and PTS are novel and efficient algorithms for matching XML query twig patterns in a parallel multi-threaded computing platform. PPS and PTS are based on the PathStack and TwigStack algorithms [1]. These algorithms employ a sophisticated search technique for limiting processing to specific subtrees. We conducted extensive experimentation with PPS and PTS. We compared PPS and PTS to the standard (sequential) PathStack and TwigStack algorithms in terms of run time (to completion). We checked their performance for varying numbers of threads. Experimental results indicate that using PPS and PTS significantly reduces the running time of queries in comparison with the PathStack/TwigStack algorithm (up to 44 times faster for DBLP queries and up to 22 times faster for XMark queries). Lila Shnaiderman, Oded Shmueli |
IEEE Trans. Knowl. Data Eng. | 1 |