Aspect Based Sentiment Analysis on a Novel Bangla Dataset Using Transformers

Rahman, Mumtahina; Fatiha, Kaniz; Rahman, Mehesum

dc.contributor.author	Rahman, Mumtahina
dc.contributor.author	Fatiha, Kaniz
dc.contributor.author	Rahman, Mehesum
dc.date.accessioned	2025-03-11T07:26:34Z
dc.date.available	2025-03-11T07:26:34Z
dc.date.issued	2024-07-05
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dc.identifier.uri	http://hdl.handle.net/123456789/2384
dc.description	Supervised by Md. Nazmul Haque, Assistant Professor, Department of Computer Science and Engineering (CSE) Islamic University of Technology (IUT) Board Bazar, Gazipur, Bangladesh This thesis is submitted in partial fulfillment of the requirement for the degree of Bachelor of Science in Software Engineering, 2024	en_US
dc.description.abstract	Abstracts are crucial summaries of a thesis, balancing brevity and clarity while ef- fectively conveying the study’s essence. Despite their importance, many writers struggle with creating abstracts that are neither too vague nor overly detailed. This abstract tackles the challenge by offering a structured approach to abstract writing, breaking down the process into five essential components: Introduction, Problem, Proposed Solution, Results, and Conclusion. Using humorous examples, the ab- stract makes the abstract-writing process engaging and accessible. Our method demonstrates significant improvements in the quality and readability of abstracts, as the humor helps demystify and simplify the process. Ultimately, effective ab- stract writing is both an art and a science, requiring precision, audience awareness, and a touch of fun to make it approachable and enjoyable.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computer Science and Engineering(CSE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.subject	ABSA, Sentiment analysis, LLM, Bengali Dataset, NLP	en_US
dc.title	Aspect Based Sentiment Analysis on a Novel Bangla Dataset Using Transformers	en_US
dc.type	Thesis	en_US