Demo Data from VLDB 2026 / reviewers in the wild / expert
Shahin Rahbariasl
dblp:240/8662
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2 · 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
2 papers |
Information retrieval · 86% Query processing and optimization · 14% | |
| Human-computer interaction and pervasive computing
1 paper |
Usability and user experience research · 100% |
Topics — the 6 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › evaluation › test collection
test collection construction |
0.8 | 2 | 2019 | Time-Limits and Summaries for Faster Relevance Assessing · SIGIR 2019 Dynamic Sampling Meets Pooling · SIGIR 2019 |
Query processing and optimization › approximate query processing
dynamic sampling |
0.4 | 1 | 2019 | Dynamic Sampling Meets Pooling · SIGIR 2019 |
Information retrieval › evaluation › effectiveness metrics
effectiveness measure estimation |
0.4 | 1 | 2019 | Dynamic Sampling Meets Pooling · SIGIR 2019 |
Information retrieval
evaluation |
0.4 | 1 | 2019 | Time-Limits and Summaries for Faster Relevance Assessing · SIGIR 2019 |
Information retrieval › evaluation
relevance judgment |
0.4 | 1 | 2019 | Time-Limits and Summaries for Faster Relevance Assessing · SIGIR 2019 |
Information retrieval
retrieval evaluation |
0.4 | 1 | 2019 | Dynamic Sampling Meets Pooling · SIGIR 2019 |
Methods — techniques the papers use, named apart from their topics
user study · 0.8xinfAP · 0.4move-to-front pooling · 0.4dynamic sampling · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Dynamic Sampling Meets PoolingabstractA team of six assessors used Dynamic Sampling (Cormack and Grossman 2018) and one hour of assessment effort per topic to form, without pooling, a test collection for the TREC 2018 Common Core Track. Later, official relevance assessments were rendered by NIST for documents selected by depth-10 pooling augmented by move-to-front (MTF) pooling (Cormack et al. 1998), as well as the documents selected by our Dynamic Sampling effort. MAP estimates rendered from dynamically sampled assessments using the xinfAP statistical evaluator are comparable to those rendered from the complete set of official assessments using the standard trec_eval tool. MAP estimates rendered using only documents selected by pooling, on the other hand, differ substantially. The results suggest that the use of Dynamic Sampling without pooling can, for an order of magnitude less assessment effort, yield information-retrieval effectiveness estimates that exhibit lower bias, lower error, and comparable ability to rank system effectiveness. Gordon V. Cormack, Haotian Zhang 0001, Nimesh Ghelani, Mustafa Abualsaud, Mark D. Smucker, Maura R. Grossman, Shahin Rahbariasl, Amira Ghenai |
SIGIR | 7 |
| 2019 | Time-Limits and Summaries for Faster Relevance AssessingabstractRelevance assessing is a critical part of test collection construction as well as applications such as high-recall retrieval that require large amounts of relevance feedback. In these applications, tens of thousands of relevance assessments are required and assessing costs are directly related to the speed at which assessments are made. We conducted a user study with 60 participants where we investigated the impact of time limits (15, 30, and 60 seconds) and document size (full length vs. short summaries) on relevance assessing. Participants were shown either full documents or document summaries that they had to judge within a 15, 30, or 60 seconds time constraint per document. We found that using a time limit as short as 15 seconds or judging document summaries in place of full documents could significantly speed judging without significantly affecting judging quality. Participants found judging document summaries with a 60 second time limit to be the easiest and best experience of the six conditions. While time limits may speed judging, the same speed benefits can be had with high quality document summaries while providing an improved judging experience for assessors. Shahin Rahbariasl, Mark D. Smucker |
SIGIR | 1 |