Discovering themes in biomedical literature using a projection-based algorithm.

ABSTRACT:

Background

The need to organize any large document collection in a manner that facilitates human comprehension has become crucial with the increasing volume of information available. Two common approaches to provide a broad overview of the information space are document clustering and topic modeling. Clustering aims to group documents or terms into meaningful clusters. Topic modeling, on the other hand, focuses on finding coherent keywords for describing topics appearing in a set of documents. In addition, there have been efforts for clustering documents and finding keywords simultaneously.

Results

We present an algorithm to analyze document collections that is based on a notion of a theme, defined as a dual representation based on a set of documents and key terms. In this w

SUBMITTER: Yeganova L 

PROVIDER: S-EPMC6048865 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature