A New Surprise Measure for Extracting Interesting Relationships between Persons
Hidetaka Kamigaito, Jingun Kwon, Young-In Song, Manabu Okumura
Abstract
One way to enhance user engagement in search engines is to suggest interesting facts to the user. Although relationships between persons are important as a target for text mining, there are few effective approaches for extracting the interesting relationships between persons. We therefore propose a method for extracting interesting relationships between persons from natural language texts by focusing on their surprisingness. Our method first extracts all personal relationships from dependency trees for the texts and then calculates surprise scores for distributed representations of the extracted relationships in an unsupervised manner. The unique point of our method is that it does not require any labeled dataset with annotation for the surprising personal relationships. The results of the human evaluation show that the proposed method could extract more interesting relationships between persons from Japanese Wikipedia articles than a popularity-based baseline method. We demonstrate our proposed method as a chrome plugin on google search.- Anthology ID:
- 2021.eacl-demos.27
- Original:
- 2021.eacl-demos.27v1
- Version 2:
- 2021.eacl-demos.27v2
- Volume:
- Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
- Month:
- April
- Year:
- 2021
- Address:
- Online
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 231–237
- Language:
- URL:
- https://aclanthology.org/2021.eacl-demos.27
- DOI:
- 10.18653/v1/2021.eacl-demos.27
- Cite (ACL):
- Hidetaka Kamigaito, Jingun Kwon, Young-In Song, and Manabu Okumura. 2021. A New Surprise Measure for Extracting Interesting Relationships between Persons. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 231–237, Online. Association for Computational Linguistics.
- Cite (Informal):
- A New Surprise Measure for Extracting Interesting Relationships between Persons (Kamigaito et al., EACL 2021)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2021.eacl-demos.27.pdf