A Multilingual Document Summarization and Deadline Detection for Educational Institutions using Openai

Alavani, Ms. Chitra

doi:https://doi.org/10.55041/ijsmt.v2i4.122

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A MULTILINGUAL DOCUMENT SUMMARIZATION AND DEADLINE DETECTION FOR EDUCATIONAL INSTITUTIONS USING OPENAI

AUTHORS:

Ms. Chitra Alavani

Mentor

Ms. Pallavi Joshi

Affiliation

Kaveri College of Arts, Science and Commerce, Pune, India

DOI: 10.55041/ijsmt.v2i4.122

CC BY 4.0 License:

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

Educational institutes receives many documents from various authorities, most of the times these are either as text-based PDFs or scanned images and are commonly written in English or regional languages. Understanding such documents can be challenging due to their length, unstructured format, and official language complexity. Many a times, users often miss important deadlines embedded within these documents as they are in pdf formats are never revisited again. The proposed system automatically generates concise summaries and extracts critical dates and deadlines using the OpenAI GPT-4o-mini large language model (LLM). The system employs a hybrid processing strategy that dynamically selects between text-based and vision-based inputs to optimize accuracy and token cost, thus increasing the accessibility to key information in the official documents.

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✓ All ethical standards met

This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.

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