A discovery system for narrative query graphs: entity-interaction-aware document retrieval.
Int J Digit Libr
; : 1-22, 2023 Apr 24.
Article
em En
| MEDLINE
| ID: mdl-37361126
Finding relevant publications in the scientific domain can be quite tedious: Accessing large-scale document collections often means to formulate an initial keyword-based query followed by many refinements to retrieve a sufficiently complete, yet manageable set of documents to satisfy one's information need. Since keyword-based search limits researchers to formulating their information needs as a set of unconnected keywords, retrieval systems try to guess each user's intent. In contrast, distilling short narratives of the searchers' information needs into simple, yet precise entity-interaction graph patterns provides all information needed for a precise search. As an additional benefit, such graph patterns may also feature variable nodes to flexibly allow for different substitutions of entities taking a specified role. An evaluation over the PubMed document collection quantifies the gains in precision for our novel entity-interaction-aware search. Moreover, we perform expert interviews and a questionnaire to verify the usefulness of our system in practice. This paper extends our previous work by giving a comprehensive overview about the discovery system to realize narrative query graph retrieval.
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01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Int J Digit Libr
Ano de publicação:
2023
Tipo de documento:
Article