A Pattern-Oriented AI-Powered Approach to Story Composition
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 15192 LNCS, Page: 135-150
2025
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
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Conference Paper Description
This paper proposes the use of narrative patterns as an effective guide to preserve thematic consistency in the composition of stories using Large Language Models (LLMs). Our approach drove inspiration from a well-accepted, thorough, and overarching classification of folklore types and the deservedly famous Monomyth characterization of heroic quests. The approach comprises both the pattern-guided composition of narratives and the creation of new patterns by applying the most specific generalization (MSG) criterion. We designed and implemented an AI-powered tool to create complex narratives in a storyboard format to demonstrate the feasibility of the proposed approach.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85210876401&origin=inward; http://dx.doi.org/10.1007/978-3-031-74353-5_10; https://link.springer.com/10.1007/978-3-031-74353-5_10; https://dx.doi.org/10.1007/978-3-031-74353-5_10; https://link.springer.com/chapter/10.1007/978-3-031-74353-5_10
Springer Science and Business Media LLC
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