Demo Data from VLDB 2026 / reviewers in the wild / expert
Toke Eskildsen
dblp:89/3967
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1Databases, data management, data science and information retrieval · 1Human-computer interaction and ubiquitous computing · 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 |
Information retrieval · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval
distributed information retrieval |
0.4 | 1 | 2019 | Solr Integration in the Anserini Information Retrieval Toolkit · SIGIR 2019 |
Information retrieval
search engines |
0.4 | 1 | 2019 | Solr Integration in the Anserini Information Retrieval Toolkit · SIGIR 2019 |
Information retrieval
evaluation |
0.1 | 1 | 2019 | Solr Integration in the Anserini Information Retrieval Toolkit · SIGIR 2019 |
Methods — techniques the papers use, named apart from their topics
solr · 0.4lucene · 0.4blacklight · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Solr Integration in the Anserini Information Retrieval ToolkitabstractAnserini is an open-source information retrieval toolkit built around Lucene to facilitate replicable research. In this demonstration, we examine different architectures for Solr integration in order to address two current limitations of the system: the lack of an interactive search interface and support for distributed retrieval. Two architectures are explored: In the first approach, Anserini is used as a frontend to index directly into a running Solr instance. In the second approach, Lucene indexes built directly with Anserini can be copied into a Solr installation and placed under its management. We discuss the tradeoffs associated with each architecture and report the results of a performance evaluation comparing indexing throughput. To illustrate the additional capabilities enabled by Anserini/Solr integration, we present a search interface built using the open-source Blacklight discovery interface. Ryan Clancy, Toke Eskildsen, Nick Ruest, Jimmy Lin |
SIGIR | 2 |
| 2005 | Design, implementation, and evaluation of the Resilient Smalltalk embedded platform
Jakob R. Andersen, Lars Bak, Steffen Grarup, Kasper V. Lund, Toke Eskildsen, Klaus Marius Hansen, Mads Torgersen |
Comput. Lang. Syst. Struct. | 5 |
| 2003 | Programming in the Kitchen
Olav W. Bertelsen, Toke Eskildsen, Werner Sperschneider |
INTERACT | 2 |