Document Detail

Deterministic Binary Vectors for Efficient Automated Indexing of MEDLINE/PubMed Abstracts.
MedLine Citation:
PMID:  23304369     Owner:  NLM     Status:  In-Data-Review    
The need to maintain accessibility of the biomedical literature has led to development of methods to assist human indexers by recommending index terms for newly encountered articles. Given the rapid expansion of this literature, it is essential that these methods be scalable. Document vector representations are commonly used for automated indexing, and Random Indexing (RI) provides the means to generate them efficiently. However, RI is difficult to implement in real-world indexing systems, as (1) efficient nearest-neighbor search requires retaining all document vectors in RAM, and (2) it is necessary to maintain a store of randomly generated term vectors to index future documents. Motivated by these concerns, this paper documents the development and evaluation of a deterministic binary variant of RI. The increased capacity demonstrated by binary vectors has implications for information retrieval, and the elimination of the need to retain term vectors facilitates distributed implementations, enhancing the scalability of RI.
Manuel Wahle; Dominic Widdows; Jorge R Herskovic; Elmer V Bernstam; Trevor Cohen
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Publication Detail:
Type:  Journal Article     Date:  2012-11-03
Journal Detail:
Title:  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium     Volume:  2012     ISSN:  1942-597X     ISO Abbreviation:  AMIA Annu Symp Proc     Publication Date:  2012  
Date Detail:
Created Date:  2013-01-10     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101209213     Medline TA:  AMIA Annu Symp Proc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  940-9     Citation Subset:  IM    
The University of Texas Health Science Center at Houston, School of Biomedical Informatics.
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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