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Anja Rathgeber

dblp:204/0136 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 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

TopicWeightPapersLastEvidence papers
Information retrieval › query processing
query spelling correction
0.312017
A Large-Scale Query Spelling Correction Corpus · SIGIR 2017
Information retrieval
evaluation
0.112017
A Large-Scale Query Spelling Correction Corpus · SIGIR 2017
Information retrieval › evaluation
test collection
0.112017
A Large-Scale Query Spelling Correction Corpus · SIGIR 2017
YearPublicationVenuePosition
2017 A Large-Scale Query Spelling Correction Corpus
abstract
We present a new large-scale collection of 54,772 queries with manually annotated spelling corrections. For 9,170 of the queries (16.74%), spelling variants that are different to the original query are proposed. With its size, our new corpus is an order of magnitude larger than other publicly available query spelling corpora. In addition to releasing the new large-scale corpus, we also provide an implementation of the winner of the Microsoft Speller Challenge from~2011 and compare it on the different publicly available corpora to spelling corrections mined from Google and Bing. This way, we also shed some light on the spelling correction performance of state-of-the-art commercial search systems.
Matthias Hagen, Martin Potthast, Marcel Gohsen, Anja Rathgeber, Benno Stein 0001
SIGIR4