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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