CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10492913" target="_blank" >RIV/00216208:11320/24:10492913 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1145/3626772.3657851" target="_blank" >https://doi.org/10.1145/3626772.3657851</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3626772.3657851" target="_blank" >10.1145/3626772.3657851</a>

Jazyk výsledku

angličtina

Název v původním jazyce

CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking

Popis výsledku v původním jazyce

We present CWRCzech, Click Web Ranking dataset for Czech, a 100M query–document Czech click dataset for relevance ranking with user behavior data collected in web search engine production. 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.

Název v anglickém jazyce

CWRCzech: 100M Query-Document Czech Click Dataset and Its Application to Web Relevance Ranking

Popis výsledku anglicky

We present CWRCzech, Click Web Ranking dataset for Czech, a 100M query–document Czech click dataset for relevance ranking with user behavior data collected in web search engine production. 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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GX20-16819X" target="_blank" >GX20-16819X: Porozumění jazyku: od syntaxe k diskurzu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval

ISBN

979-8-4007-0431-4

ISSN

—

e-ISSN

—

Počet stran výsledku

11

Strana od-do

1221-1231

Název nakladatele

Association for Computing Machinery

Místo vydání

New York, NY, USA

Místo konání akce

Washington DC, USA

Datum konání akce

14. 7. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001273410001030