DeepMeSH: deep semantic representation for improving large-scale MeSH indexing.

ABSTRACT:

Motivation

Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval. Large-scale MeSH indexing has two challenging aspects: the citation side and MeSH side. For the citation side, all existing methods, including Medical Text Indexer (MTI) by National Library of Medicine and the state-of-the-art method, MeSHLabeler, deal with text by bag-of-words, which cannot capture semantic and context-dependent information well.

Methods

We propose DeepMeSH that incorporates deep semantic information for large-scale MeSH indexing. It addresses the two challenges in both citation and MeSH sides. The citation side challenge is solved by a new deep semantic rep

SUBMITTER: Peng S 

PROVIDER: S-EPMC4908368 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature