Topic detection using paragraph vectors to support active learning in systematic reviews.

ABSTRACT: Systematic reviews require expert reviewers to manually screen thousands of citations in order to identify all relevant articles to the review. Active learning text classification is a supervised machine learning approach that has been shown to significantly reduce the manual annotation workload by semi-automating the citation screening process of systematic reviews. In this paper, we present a new topic detection method that induces an informative representation of studies, to improve the performance of the underlying active learner. Our proposed topic detection method uses a neural network-based vector space model to capture semantic similarities between documents. We firstly represent documents within the vector space, and cluster the documents into a predefined number of clusters. The

SUBMITTER: Hashimoto K 

PROVIDER: S-EPMC4981645 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature