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Adriel Dean-Hall

dblp:160/1757 · DBLP profile ↗
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2ranked-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 · 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
1 paper
Information retrieval · 100%

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

TopicWeightPapersLastEvidence papers
Information retrieval
evaluation
0.212015
On the Reusability of Open Test Collections · SIGIR 2015
Information retrieval › evaluation › test collection › test collection construction
pooling
0.212015
On the Reusability of Open Test Collections · SIGIR 2015
Information retrieval › evaluation
test collection
0.212015
On the Reusability of Open Test Collections · SIGIR 2015
YearPublicationVenuePosition
2015 The Power of Contextual Suggestion
Adriel Dean-Hall, Charles L. A. Clarke
ECIR1
2015 On the Reusability of Open Test Collections
abstract
Creating test collections for modern search tasks is increasingly more challenging due to the growing scale and dynamic nature of content, and need for richer contextualization of the statements of request. To address these issues, the TREC Contextual Suggestion Track explored an open test collection, where participants were allowed to submit any web page as a result for a personalized venue recommendation task. This prompts the question on the reusability of the resulting test collection: How does the open nature affect the pooling process? Can participants reliably evaluate variant runs with the resulting qrels? Can other teams evaluate new runs reliably? In short, does the set of pooled and judged documents effectively produce a post hoc test collection? Our main findings are the following: First, while there is a strongly significant rank correlation, the effect of pooling is notable and results in underestimation of performance, implying the evaluation of non-pooled systems should be done with great care. Second, we extensively analyze impacts of open corpus on the fraction of judged documents, explaining how low recall affects the reusability, and how the personalization and low pooling depth aggravate that problem. Third, we outline a potential solution by deriving a fixed corpus from open web submissions.
Seyyed Hadi Hashemi, Charles L. A. Clarke, Adriel Dean-Hall, Jaap Kamps, Julia Kiseleva
SIGIR3