BioDR: Semantic indexing networks for biomedical document retrieval

Anália Lourenço, Rafael Carreira, Daniel Glez-Peña, José R. Méndez, Sónia Carneiro, Luis M. Rocha, Fernando Díaz, Eugénio C. Ferreira, Isabel Rocha, Florentino Fdez-Riverola
2010 Expert systems with applications  
In Biomedical research, retrieving documents that match an interesting query is a task performed quite frequently. Typically, the set of obtained results is extensive containing many non-interesting documents and consists in a flat list, i.e., not organized or indexed in any way. This work proposes BioDR, a novel approach that allows the semantic indexing of the results of a query, by identifying relevant terms in the documents. These terms emerge from a process of Named Entity Recognition that
more » ... annotates occurrences of biological terms (e.g. genes or proteins) in abstracts or full-texts. The system is based on a learning process that builds an Enhanced Instance Retrieval Network (EIRN) from a set of manually classified documents, regarding their relevance to a given problem. The resulting EIRN implements the semantic indexing of documents and terms, allowing for enhanced navigation and visualization tools, as well as the assessment of relevance for new documents.
doi:10.1016/j.eswa.2009.10.044 fatcat:f3mth5maujh7blsv7is2jptjra