• Aggregating semantic informati...

Treffer: Aggregating semantic information nuggets for answering clinical queries

Title:
Aggregating semantic information nuggets for answering clinical queries
Authors:
Znaidi, Eya, Tamine, Lynda, Latiri, Chiraz
Contributors:
Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse - Jean Jaurès (UT2J), Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse III - Paul Sabatier (UT3), Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse III - Paul Sabatier (UT3), Communauté d'universités et établissements de Toulouse (Comue de Toulouse), Recherche d’Information et Synthèse d’Information (IRIT-IRIS), Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Université Toulouse Capitole (UT Capitole), Université de Tunis
Source:
31st Annual ACM Symposium on Applied Computing (SAC 2016). :1041-1047
Publisher Information:
CCSD; ACM, 2016.
Publication Year:
2016
Collection:
collection:UNIV-TLSE2
collection:UNIV-TLSE3
collection:CNRS
collection:UT1-CAPITOLE
collection:IRIT
collection:IRIT-IRIS
collection:IRIT-GD
collection:TOULOUSE-INP
collection:UNIV-UT3
collection:UT3-INP
collection:UT3-TOULOUSEINP
Subject Terms:
Clinical Queries, Medical information retrieval, Semantic Query representation, [INFO.INFO-IT]Computer Science [cs], Information Theory [cs.IT], [INFO.INFO-IR]Computer Science [cs], Information Retrieval [cs.IR]
Subject Geographic:
Pise, Italy
Original Identifier:
HAL: hal-04109459
Document Type:
Konferenz conferenceObject<br />Conference papers
Language:
English
ISBN:
978-1-4503-3739-7
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.1145/2851613.2851694
DOI:
10.1145/2851613.2851694
Access URL:
https://hal.science/hal-04109459
https://hal.science/hal-04109459v1/document
https://hal.science/hal-04109459v1/file/znaidi_17073.pdf
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.hal.04109459v1
Database:
HAL

Weitere Informationen

In this paper, we address the issue of answering PICO clinical queries formulated within the Evidence Based Medicine framework. Answering clinical questions gives raise to numerous challenges among wich term ambiguity and relevane estimation based on the distribution of the query facets in the documents. The contributions of this work include (1) a new algorithm for query refinement based on the semantic mapping of each facet of the query to a reference terminology and (2) a new document ranking model based on a prioritized aggregation operator that leverages the importance of each facet with regard to a candidate relevant document. The effectiveness of our PICO-based search approach is empirically evaluated using a clinical retrieval collection including 423 queries and more than 1.2 million of medical abstracts from PubMed. The experimental results show that our approach for PICO query answering significantly overpasses state-of-the-art document ranking models.