Adelaida Zuluaga Cajiao
ABSTRACT
The growing amount of available data in the biomedical domain turns out to be beneficial for decision-making, but a sufficiently accurate DR system is required. Plenty of NLP techniques and models have been proposed for semantic similarity in DR, but few of them have been able to consider the variations of the language and relationship between distant words in texts. This work is focused on formulating a Graph-based Similarity for DR method (GBS-DR) for the biomedical domain and comparing the obtained results with traditional DR paradigms. The graph-based methods were selected to prove the importance of analyzing the semantic, syntactic, and long-distant word relationships in texts. It will be demonstrated that through the graph's topology the system can extract the structural information of documents, which solves relevant issues that are faced in this research area.
CCS CONCEPTS • Information Systems • Information Retrieval • Retrieval Models and Ranking • Learning to Rank
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Index Terms
- Graph-based Similarity for Document Retrieval in the Biomedical Domain
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