Conference proceeding
Narrative Hermeneutic Circle: Improving Character Role Identification from Natural Language Text via Feedback Loops
PROCEEDINGS OF THE TWENTY-FOURTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI), pp.2517-2523
01 Jan 2015
Abstract
While most natural language understanding systems rely on a pipeline-based architecture, certain human text interpretation methods are based on a cyclic process between the whole text and its parts: the hermeneutic circle. In the task of automatically identifying characters and their narrative roles, we propose a feedback-loop-based approach where the output of later modules of the pipeline is fed back to earlier ones. We analyze this approach using a corpus of 21 Russian folktales. Initial results show that feeding back high-level narrative information improves the performance of some NLP tasks.
Metrics
1 Record Views
Details
- Title
- Narrative Hermeneutic Circle: Improving Character Role Identification from Natural Language Text via Feedback Loops
- Creators
- Josep Valls-Vargas - Drexel Univ, Comp Sci, Philadelphia, PA 19104 USAJichen Zhu - Drexel Univ, Digital Media, Philadelphia, PA 19104 USASantiago Ontanon - Drexel Univ, Comp Sci, Philadelphia, PA 19104 USA
- Contributors
- Q Yang (Editor)M Wooldridge (Editor)
- Publication Details
- PROCEEDINGS OF THE TWENTY-FOURTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI), pp.2517-2523
- Conference
- TWENTY-FOURTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI), 24th
- Publisher
- Ijcai-Int Joint Conf Artif Intell
- Number of pages
- 7
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Digital Media; Computer Science (Computing)
- Identifiers
- 991019170456904721
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Interdisciplinary Applications