Learning to Enrich Query Representation with Pseudo-Relevance Feedback for Cross-lingual Retrieval.

Ramraj Chandradevan|Eugene Yang|Mahsa Yarmohammadi|Eugene Agichtein


Anthology ID:DBLP:conf/sigir/ChandradevanYYA22
Volume:SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022
Year:2022
Venue:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Publisher:ACM
Pages:1790-1795
URL:https://doi.org/10.1145/3477495.3532013
DOI:https://doi.org/10.1145/3477495.3532013
DBLP:conf/sigir/ChandradevanYYA22
BibTeX:
@inproceedings{chandradevan-2022-learning, author = {Ramraj Chandradevan and Eugene Yang and Mahsa Yarmohammadi and Eugene Agichtein}, editor = {Enrique Amig\'{o} and Pablo Castells and Julio Gonzalo and Ben Carterette and J. Shane Culpepper and Gabriella Kazai}, title = {{Learning to Enrich Query Representation with Pseudo-Relevance Feedback for Cross-lingual Retrieval}}, booktitle = {{SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022}}, pages = {1790--1795}, publisher = {ACM}, year = {2022}, url = {https://doi.org/10.1145/3477495.3532013}, doi = {https://doi.org/10.1145/3477495.3532013} }