Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Context Vectors: A Step Toward a "Grand Unified Representation"
Hybrid Neural Systems, revised papers from a workshop
Information Retrieval: A Health and Biomedical Perspective
Information Retrieval: A Health and Biomedical Perspective
A Linear Least Squares Fit mapping method for information retrieval from natural language texts
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
Journal of Biomedical Informatics
Use of Medical Subject Headings (MeSH) in Portuguese for categorizing web-based healthcare content
Journal of Biomedical Informatics
Cross-lingual random indexing for information retrieval
SLSP'13 Proceedings of the First international conference on Statistical Language and Speech Processing
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The rapid growth of biomedical literature is evident in the increasing size of the MEDLINE research database. Medical Subject Headings (MeSH), a controlled set of keywords, are used to index all the citations contained in the database to facilitate search and retrieval. This volume of citations calls for efficient tools to assist indexers at the US National Library of Medicine (NLM). Currently, the Medical Text Indexer (MTI) system provides assistance by recommending MeSH terms based on the title and abstract of an article using a combination of distributional and vocabulary-based methods. In this paper, we evaluate a novel approach toward indexer assistance by using nearest neighbor classification in combination with Reflective Random Indexing (RRI), a scalable alternative to the established methods of distributional semantics. On a test set provided by the NLM, our approach significantly outperforms the MTI system, suggesting that the RRI approach would make a useful addition to the current methodologies.