Demo Data from SIGIR 2026 / reviewers in the wild / expert
Steve Moulton
dblp:59/1857
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2
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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
knowledge base |
0.1 | 1 | 2012 | BESC knowledgebase public portal · Bioinform. 2012 |
Methods — techniques the papers use, named apart from their topics
data integration · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | BESC knowledgebase public portalabstractUNLABELLED: The BioEnergy Science Center (BESC) is undertaking large experimental campaigns to understand the biosynthesis and biodegradation of biomass and to develop biofuel solutions. BESC is generating large volumes of diverse data, including genome sequences, omics data and assay results. The purpose of the BESC Knowledgebase is to serve as a centralized repository for experimentally generated data and to provide an integrated, interactive and user-friendly analysis framework. The Portal makes available tools for visualization, integration and analysis of data either produced by BESC or obtained from external resources. AVAILABILITY: http://besckb.ornl.gov. Mustafa H. Syed, Tatiana V. Karpinets, Morey Parang, Michael R. Leuze, Doug Hyatt, Steven D. Brown, Steve Moulton, Michael D. Galloway, Edward C. Uberbacher |
Bioinform. | 8 |
| 2006 | Embedding Rules in a Pre-Hospital Mobile DatabaseabstractHealthcare systems, especially Emergency Medical Services systems, will greatly benefit from new developments in mobile database technology. One area that has received little attention is the representation of rules for accurate data capture in a mobile environment. Herein we describe the use of semantic web technologies to embed rules in a mobile database. The rules are presented as Topic Maps and are accessed by a Semantic Interpretation Layer (SIL). Embedding rules in mobile healthcare applications will ensure accurate patient data capture and speed the creation of large knowledge bases of patient information. These knowledge bases will, in turn, support the creation of intelligent patient care systems that can not only define, but begin to anticipate patient care needs. Nada Hashmi, Dan Corwin, Dan Myung, Mark Gaynor, Valmeek Kudesia, William Tollefsen, G. Shankaranarayanan, Steve Moulton |
AICCSA | 8 |