Abstract
Graphs have long been proposed as a tool to browse and navigate in a collection of documents in order to support exploratory search. Many techniques to automatically extract different types of graphs, showing for example entities or concepts and different relationships between them, have been suggested. While experimental evidence that they are indeed helpful exists for some of them, it is largely unknown which type of graph is most helpful for a specific exploratory task. However, carrying out experimental comparisons with human subjects is challenging and time-consuming. Towards this end, we present the GraphDocExplore framework. It provides an intuitive web interface for graph-based document exploration that is optimized for experimental user studies. Through a generic graph interface, different methods to extract graphs from text can be plugged into the system. Hence, they can be compared at minimal implementation effort in an environment that ensures controlled comparisons. The system is publicly available under an open-source license.- Anthology ID:
- D17-2004
- Volume:
- Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Editors:
- Lucia Specia, Matt Post, Michael Paul
- Venue:
- EMNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 19–24
- Language:
- URL:
- https://aclanthology.org/D17-2004
- DOI:
- 10.18653/v1/D17-2004
- Cite (ACL):
- Tobias Falke and Iryna Gurevych. 2017. GraphDocExplore: A Framework for the Experimental Comparison of Graph-based Document Exploration Techniques. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 19–24, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- GraphDocExplore: A Framework for the Experimental Comparison of Graph-based Document Exploration Techniques (Falke & Gurevych, EMNLP 2017)
- PDF:
- https://preview.aclanthology.org/naacl24-info/D17-2004.pdf