Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 24. Juni 2018)
1Tamine, L. ; Chouquet, C.: On the impact of domain expertise on query formulation, relevance assessment and retrieval performance in clinical settings.
In: Information processing and management. 53(2017) no.2, S.332-350.
Abstract: The large volumes of medical information available on the web may provide answers for a wide range of users attempting to solve health-related problems. While experts generally utilize reliable resources for diagnosis search and professional development, novices utilize different (social) web resources to obtain information that helps them manage their health or the health of people who they care for. A diverse number of related search topics address clinical diagnosis, advice searching, information sharing, connecting with experts, etc. This paper focuses on the extent to which expertise can impact clinical query formulation, document relevance assessment and retrieval performance in the context of tailoring retrieval models and systems to experts vs. non-experts. The results show that medical domain expertise 1) plays an important role in the lexical representations of information needs; 2) significantly influences the perception of relevance even among users with similar levels of expertise and 3) reinforces the idea that a single ground truth does not exist, thereby leading to the variability of system rankings with respect to the level of user's expertise. The findings of this study presents opportunities for the design of personalized health-related IR systems, but also for providing insights about the evaluation of such systems.
Inhalt: Vgl.: http://www.sciencedirect.com/science/article/pii/S030645731630303X [http://dx.doi.org/10.1016/j.ipm.2016.11.004].
2Tamine, L. ; Chouquet, C. ; Palmer, T.: Analysis of biomedical and health queries : lessons learned from TREC and CLEF evaluation benchmarks.
In: Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2626-2642.
Abstract: A large body of research work examined, from both the query side and the user behavior side, the characteristics of medical- and health-related searches. One of the core issues in medical information retrieval (IR) is diversity of tasks that lead to diversity of categories of information needs and queries. From the evaluation perspective, another related and challenging issue is the limited availability of appropriate test collections allowing the experimental validation of medically task oriented IR techniques and systems. In this paper, we explore the peculiarities of TREC and CLEF medically oriented tasks and queries through the analysis of the differences and the similarities between queries across tasks, with respect to length, specificity, and clarity features and then study their effect on retrieval performance. We show that, even for expert oriented queries, language specificity level varies significantly across tasks as well as search difficulty. Additional findings highlight that query clarity factors are task dependent and that query terms specificity based on domain-specific terminology resources is not significantly linked to term rareness in the document collection. The lessons learned from our study could serve as starting points for the design of future task-based medical information retrieval frameworks.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23351/abstract.
Objekt: TREC ; CLEF