Multidisciplinary, Arts and Humanities, Education, Literature and Literary Theory
3
Scopus Publications
Scopus Publications
Natural Language Processing-Based Literary Analysis Framework for Linguistic Nuance Detection in English Literature Vishnu Vandana Devi V, I. M. Khairdi, Shikha Dutt Sharma, Sonia Gouri, Gourika Sharma, Sashka Jovanovska Proceedings 2025 International Conference on Recent Innovation in Science Engineering and Technology Icriset 2025, 2025 The present paper introduces a Natural Language Processing (NLP)-Based Literary Analysis Framework that works to identify the linguistic elements in English literature. The framework leverages state-of-the-art Contextual Word Embeddings in BERT (Bidirectional Encoder Representations of Transformers), a state-of-the-art NLP model to learn the semantic nuances in literary works. Using BERT that allows identifying contextual meanings of individual words relying on the text around it, the framework can extract such complex linguistic features as irony, metaphors, and emotions in narratives. This method enables us to identify sophistication in language used important phenomena that cannot be identified in the conventional literary analysis, thus a more insightful interpretation of the language and style of an author. Implementation of BERT means that we can identify literary devices, emotional changes and thematic developments within a text which are incredibly important in actually interpreting the text beyond the generally accepted interpretations. Through the marriage of computers and linguistics this framework finds a piece of the puzzle as far as literary analysis. This framework presents a new way of viewing English literature through modern NLP techniques.
Knowledge-Based Recommendation for Subject Allocation Using Artificial Neural Network in Higher Education Nitin Kumar Saxena, Bhavesh Kumar Chauhan, Sonia Gouri, Ashwani Kumar, Anmol Gupta IEEE Transactions on Education, 2023 Contribution: The proposed work carries out the training and testing of the available data through an artificial neural network and develops a model to allocate the subject for maximum outcome. The system also provides percentagewise correlation among all the possible subjects of best fit to allocate among the faculty members. Background: Data mining and machine learning tools have amazed all professionals with their fast, accurate, precise, and feasible results. While their results cannot be directly superimposed on all education systems, they certainly provide ideas for improving teaching pedagogy based on the requirements and capabilities of the system. Intended Outcomes: The subject allocation among the faculty members in engineering studies plays a crucial role in teaching and training the students in the best possible way from the point of view of outcome-based education. The objective of this article is to present an effective model for subject allocation to faculty members based on various factors. Application Design: Faculty members have their diversified strengths because of their involvement in different institute activities. An appropriate subject allocation mechanism for any faculty accumulating the knowledge of an individual’s responsibilities and area of interest can support more significantly in achieving the course outcomes. Findings: 1) Subject allocation based on individuals’ involvement in academics, administrative, and research domains; 2) Subject allocation based on qualifications and experiences for engendering the outcome; and 3) A user-friendly model development for applying at an individual, department, or even at the institute level.
Impact of Advertising on Shopping Behaviour: A Study of Mobile Phones Sapna Yadav, Meenakshi Tyagi, Himani Grewal, Sonia Gouri, Tanushree Sanwal Sustainable Technology for Society 5 0 Case Studies Examples and Advanced Research Findings, 2023 Consumer behavior (CB) is highly influenced when any market investor promotes their products through different media outlets. The ad throughout the media has a unique design that involves customers in a different practice. Digital inclusion has prompted changes in buyer media practices. Therefore, a more profound comprehension of promotions on various media stages and the impact on CB should be assembled. Advertising efforts are targeted at the consumer and are in control of everything available to the public. Spending in India is expected to improve by 12.5% in 2018 from 9.6% last year. Present research focuses on a variety of ad factors that affect the performance of each purchase. The people interviewed in this study were college students. It is a well-known fact that the youth of our country are the biggest buyers of smart phones. The conclusion of this study is based on key data collected from students of various colleges in Delhi NCR.
