Dataset origin: https://researchdata.tuwien.at/records/y60e9-k9b51 & https://researchdata.tuwien.ac.at/records/xr350-79683

Description

Train set

The collection consists of queries and documents provided by the Qwant search Engine (https://www.qwant.com). The queries, which were issued by the users of Qwant, are based on the selected trending topics. The documents in the collection were selected with respect to these queries using the Qwant click model. Apart from the documents selected using this model, the collection also contains randomly selected documents from the Qwant index. All the data were collected over January 2023. In total, the collection contains 599 train queries, with corresponding 9,785 relevance assessments coming from the Qwant click model. The set of documents consist of 2,049,729 downloaded, cleaned and filtered Web Pages. Apart from their original French versions, the collection also contains translations of the webpages and queries into English. The collection serves as the official training collection for the 2024 LongEval Information Retrieval Lab (https://clef-longeval.github.io/) organised at CLEF.

Test set

The collection consists of queries and documents provided by the Qwant search Engine (https://www.qwant.com). The queries, which were issued by the users of Qwant, are based on the selected trending topics. The documents in the collection were selected with respect to these queries using the Qwant click model. Apart from the documents selected using this model, the collection also contains randomly selected documents from the Qwant index. All the data was collected over June 2023 and August 2023. In total, the collection contains 1,925 test queries. The set of documents consist of 4,321,642 downloaded, cleaned and filtered Web Pages. Apart from their original French versions, the collection also contains translations of the webpages and queries into English. The collection serves as the official test collection for the 2024 LongEval Information Retrieval Lab (https://clef-longeval.github.io/) organised at CLEF.

Citation

 @misc{fink_piroi_devaud_galuščáková_gonzalez-saez_iommi_mulhem_goeuriot_popel_el-ebshihy_2024, title={LongEval 2024 Train Collection}, DOI={10.48436/y60e9-k9b51}, abstractNote={The collection consists of queries and documents provided by the Qwant search Engine (https://www.qwant.com). The queries, which were issued by the users of Qwant, are based on the selected trending topics. The documents in the collection were selected with respect to these queries using the Qwant click model. Apart from the documents selected using this model, the collection also contains randomly selected documents from the Qwant index. All the data were collected over January 2023. In total, the collection contains 599 train queries, with corresponding 9,785 relevance assessments coming from the Qwant click model. The set of documents consist of 2,049,729 downloaded, cleaned and filtered Web Pages. Apart from their original French versions, the collection also contains translations of the webpages and queries into English. The collection serves as the official training collection for the 2024 LongEval Information Retrieval Lab (https://clef-longeval.github.io/) organised at CLEF. The data is released under the Qwant LongEval Attribution-NonCommercial-ShareAlike License.}, publisher={TU Wien}, author={Fink, Tobias and Piroi, Florina and Devaud, Romain and Galuščáková, Petra and Gonzalez-Saez, Gabriela and Iommi, David and Mulhem, Philippe and Goeuriot, Lorraine and Popel, Martin and El-Ebshihy, Alaa}, year={2024}, month={avr} }

License

https://lindat.mff.cuni.cz/repository/xmlui/page/Qwant_LongEval_BY-NC-SA_License