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
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
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