Exploiting inference from semantic annotations for information retrieval
Data(s) |
2014
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Resumo |
The increasing amount of information that is annotated against standardised semantic resources offers opportunities to incorporate sophisticated levels of reasoning, or inference, into the retrieval process. In this position paper, we reflect on the need to incorporate semantic inference into retrieval (in particular for medical information retrieval) as well as previous attempts that have been made so far with mixed success. Medical information retrieval is a fertile ground for testing inference mechanisms to augment retrieval. The medical domain offers a plethora of carefully curated, structured, semantic resources, along with well established entity extraction and linking tools, and search topics that intuitively require a number of different inferential processes (e.g., conceptual similarity, conceptual implication, etc.). We argue that integrating semantic inference in information retrieval has the potential to uncover a large amount of information that otherwise would be inaccessible; but inference is also risky and, if not used cautiously, can harm retrieval. |
Identificador | |
Publicador |
ACM |
Relação |
DOI:10.1145/2663712.2666197 Zuccon, Guido, Koopman, Bevan, & Bruza, Peter D. (2014) Exploiting inference from semantic annotations for information retrieval. In Proceedings of the 7th International Workshop on Exploiting Semantic Annotations in Information Retrieval ( ESAIR '14), ACM, Shanghai, China, pp. 43-45. |
Direitos |
Copyright 2014 ACM |
Fonte |
School of Information Systems; Science & Engineering Faculty |
Tipo |
Conference Paper |