Work

Citation Analysis with Neural Attention Models

Year: 2016

Type: conference-paper

Abstract: Automated citation analysis (ACA) can be important for many applications including author ranking and literature based information retrieval, extraction, summarization and question answering.In this study, we developed a new compositional attention network (CAN) model to integrate local and global attention representations with a hierarchical attention mechanism.Training on a new benchmark corpus we built, our evaluation shows that the CAN model performs consistently well on both citation classification and sentiment analysis tasks.

Source: International Workshop on Health Text Mining and Information Analysis (LOUHI)

DOI: 10.18653/v1/w16-6109

Authors: Tsendsuren Munkhdalai, John Lalor, Hong Yu

Language: English

Topic: scientometrics and bibliometrics research

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Funders: National Institutes of Health, National Heart, Lung, and Blood Institute

Award: EHR Anticoagulants Pharmacovigilance

OpenAlex ID: W2565730199