Title : Computational Models for Story Plot Generation and Summarisation

Type of Material: Thesis
Title: Computational Models for Story Plot Generation and Summarisation
Researcher: Khalpada, Purvish
Guide: Garg, Sanjay
Department: Institute of Technology
Publisher: Nirma University, Ahmedabad
Place: Ahmedabad
Year: 2023
Language: English
Subject: Computational Models
Computer Science
Computer Science Artificial Intelligence
Engineering and Technology
story plot generation
Computer Science and Information Technology
Engineering and Technology
Dissertation/Thesis Note: PhD; Institute of Technology, Nirma University, Ahmedabad, Ahmedabad; 2023
Fulltext: Shodhganga

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035__|a(IN-AhILN)th_456621
040__|aNIRU_382481|dIN-AhILN
041__|aeng
100__|aKhalpada, Purvish|eResearcher
110__|aInstitute of Technology|bNirma University, Ahmedabad|dAhmedabad|ein|0U-0146
245__|aComputational Models for Story Plot Generation and Summarisation
260__|aAhmedabad|bNirma University, Ahmedabad|c2023
300__|dDVD
502__|cInstitute of Technology, Nirma University, Ahmedabad, Ahmedabad|d2023|bPhD
518__|d2023|oDate of Award
518__|oDate of Registration|d2016
520__|aStory plot generation and summarisation are two open problems in natural language generation and understanding. Initial approaches to story generation and summarisation relied heavily on extensive knowledge engineering. To overcome this expensive dependency, many researchers have designed neural-based approaches. However, the current neural models have their fair share of weaknesses. Their generated story lacks many characteristics like a central theme, purpose, etcetera. It would hardly engage any reader. Additionally, these models are very opaque, hardly shed any light on the storytelling process, and are far from explainable AI. This thesis proposes a mathematical model of story plot generation and summarization. We hypothesise that a story is a series of states which requires certain conditions to be met before the transition of the states. Therefore, we use Petri net as a causal backbone of the model. We populate its knowledge from open data sources like ConceptNet and use a transformer model like Come
650__|aComputer Science and Information Technology|2UGC
650__|aEngineering and Technology|2AIU
653__|aComputational Models
653__|aComputer Science
653__|aComputer Science Artificial Intelligence
653__|aEngineering and Technology
653__|astory plot generation
700__|eGuide|aGarg, Sanjay
856__|uhttp://shodhganga.inflibnet.ac.in/handle/10603/509897|yShodhganga
905__|afromsg

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