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Lenka Lasonová

dblp:378/5668 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0003-7524-0367ORCID · reported

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

Databases, data management, data science and information retrieval · 1 · 1 since 2021

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 · 94% Web and social media mining · 6%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › query log analysis
clickthrough data
0.812024
CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking · SIGIR 2024
Information retrieval
evaluation
0.812024
CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking · SIGIR 2024
Information retrieval › ranking › search ranking
relevance ranking
0.812024
CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking · SIGIR 2024
Information retrieval › evaluation
test collection
0.812024
CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking · SIGIR 2024
Information retrieval
web search
0.812024
CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking · SIGIR 2024
Web and social media mining
user behavior analysis
0.212024
CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking · SIGIR 2024
YearPublicationVenuePosition
2024 CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking
abstract
We present CWRCzech, Click Web Ranking dataset for Czech, a 100M query-document Czech click dataset for relevance ranking with user behavior data collected from search engine logs of Seznam.cz. To the best of our knowledge, CWRCzech is the largest click dataset with raw text published so far. It provides document positions in the search results as well as information about user behavior: 27.6M clicked documents and 10.8M dwell times. In addition, we also publish a manually annotated Czech test for the relevance task, containing nearly 50k query-document pairs, each annotated by at least 2 annotators. Finally, we analyze how the user behavior data improve relevance ranking and show that models trained on data automatically harnessed at sufficient scale can surpass the performance of models trained on human annotated data. CWRCzech is published under an academic non-commercial license and is available to the research community at https://github.com/seznam/CWRCzech.
Josef Vonásek, Milan Straka, Rostislav Krc, Lenka Lasonová, Ekaterina Egorova, Jana Straková, Jakub Náplava
SIGIR4