@inproceedings{7cc0d2b3471c434ea0f6525112b5c5c5,
title = "RULKNE: Representing User Knowledge State in Search-as-Learning with Named Entities",
abstract = "A reliable representation of the user's knowledge state during a learning search session is crucial to understand their real information needs. When a search system is aware of such a state, it can adapt the search results and provide greater support for the user's learning objectives. A common practice to track the user's knowledge state is to consider the content of the documents they read during their search session(s). However, most current work ignores entity mentions in the documents, which, when linked to knowledge graphs, can be a source of valuable information regarding the user's knowledge. To fill this gap, we extend RULK - Representing User Knowledge in Search-as-Learning - with entity linking capabilities. The extended framework RULK represents and tracks user knowledge as a collection of such entities. It eventually estimates the user knowledge gain - learning outcome - by measuring the similarity between the represented knowledge and the learning objective. We show that our methods allow for up to 10% improvements when estimating user knowledge gains. ",
keywords = "Interactive IR, Named Entities, Retrieval system, Search-As-Learning, User Knowledge",
author = "{El Zein}, Dima and Arthur C{\^a}mara and {Da Costa Pereira}, C{\'e}lia and Andrea Tettamanzi",
note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 8th ACM SIGIR Conference on Human Information Interaction and Retrieval, CHIIR 2023 ; Conference date: 19-03-2023 Through 23-03-2023",
year = "2023",
doi = "10.1145/3576840.3578330",
language = "English",
series = "CHIIR 2023 - Proceedings of the 2023 Conference on Human Information Interaction and Retrieval",
publisher = "Association for Computing Machinery (ACM)",
pages = "388--393",
booktitle = "CHIIR 2023 - Proceedings of the 2023 Conference on Human Information Interaction and Retrieval",
address = "United States",
}