@inproceedings{edaf9cd9f5264c6d91048de7b9068587,
title = "Conversational Search with Random Walks over Entity Graphs",
abstract = "The entities that emerge during a conversation can be used to model topics, but not all entities are equally useful for this task. Modeling the conversation with entity graphs and predicting each entity's centrality in the conversation provides additional information that improves the retrieval of answer passages for the current question. Experiments show that using random walks to estimate entity centrality on conversation entity graphs improves top precision answer passage ranking over competitive transformer-based baselines.",
keywords = "conversational search, entity graph, named-entities, passage retrieval",
author = "Gustavo Gon{\c c}alves and Jo{\~a}o Magalh{\~a}es and Jamie Callan",
note = "info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04516%2F2020/PT# info:eu-repo/grantAgreement/FCT/5665-PICT/CMUP-ERI%2FTIC%2F0046%2F2014/PT# info:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F140924%2F2018/PT# Funding Information: This work has been partially funded by the Amazon Science - TaskBot Prize Challenge and the CMU|Portugal projects iFetch (LISBOA-01-0247-FEDER-045920). Any opinions, findings, and conclusions in this paper are the authors{\textquoteright} and do not necessarily reflect those of the sponsors. Publisher Copyright: {\textcopyright} 2023 Owner/Author.; 9th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2023 ; Conference date: 23-07-2023 Through 23-07-2023",
year = "2023",
month = aug,
day = "9",
doi = "10.1145/3578337.3605125",
language = "English",
isbn = "979-8-4007-0073-6",
series = "ICTIR: Theory of Information Retrieval",
publisher = "ACM - Association for Computing Machinery",
pages = "77--85",
booktitle = "ICTIR 2023",
address = "United States",
}