Academic Community Explorer (ACE) for Syntactic, Semantic and Pragmatic Document Analysis

Akansha Bhardwaj, Dominique Mercier, Hisham Hashmi, Sheraz Ahmed, Andreas Dengel

In: IAPR International Conference on Document Analysis and Recognition. International Conference on Document Analysis and Recognition (ICDAR-2017) 14th November 9-15 Kyoto Japan Seiten 262-267 5 ISBN 978-1-5386-3586-5 IEEE 11/2017.


This paper presents a novel Academic Community Explorer (ACE) which performs syntactic, semantic and pragmatic document analysis of scientific publications. Firstly, ACE uses syntactic structure to extract relevant information from a scientific document. Secondly, semantic analysis is performed to derive an article based co-authorship and citation network. Finally, ACE uses these document based networks to build a complete community network for pragmatic analysis. Furthermore, scientometric analysis is performed to extract the pragmatics by analyzing authors and publication community networks through micro and macro indicators. Two novel micro indicators Senti-Index, reflecting the sentiment present in citations and, Overlap index, reflecting community behavior have been introduced. This is a step in the direction of automatic qualitative assessment of scientific documents. In addition, ACE provides a rich visualization interface which helps in exploratory analysis of the community to identify hidden patterns, e.g, isolated small groups in the community which collaborate and cite each other frequently. A feasibility study is performed on the corpus of ICDAR publications from 1993-2015 to show the insights and benefits of the ACE framework. The results reveals that ICDAR is a highly collaborative community which has most likely arrived at its 'phase transition' stage with 70% of the community closely connected to each other.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence