Measuring the Structural and Conceptual Similarity of Folktales using Plot Graphs

2Citations
Citations of this article
76Readers
Mendeley users who have this article in their library.

Abstract

This paper presents an approach to organizing folktales based on a data structure called a plot graph, which captures the narrative flow of events in a folktale. The similarity between two folktales can be computed as the structural similarity between their corresponding plot graphs. This is performed using the well-known Needleman-Wunsch algorithm. To test the efficacy of this approach, experiments are carried out using a small collection of 24 folktales grouped into 5 categories based on the Aarne-Thompson index. The best result is obtained by combining the proposed structural-based similarity measure with a more conventional bag of words vector space model, where 19 out of the 24 folktales (79.16%) yield higher average similarity with folktales within their respective categories as opposed to across categories. c 2015 Association for Computational Linguistics and The Asian Federation of Natural Language Processing.

Cite

CITATION STYLE

APA

Lestari, V. A., & Manurung, R. (2015). Measuring the Structural and Conceptual Similarity of Folktales using Plot Graphs. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (Vol. 2015-text, pp. 25–33). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w15-3704

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free