Jul 2026· IDEALIS : InDonEsiA journaL Information System· 0 citations· 26 references
TL;DR
An integrated transformer-based one-gate architecture that combines document routing, academic document summarization, and conversational assistance in a single service platform, offering practical value for reducing fragmented academic information services and methodological value as a reference model for higher education NLP implementation is developed.
Abstract
The rapid digitalization of higher education requires academic information services that are fast, integrated, and accessible. Fragmented service channels, high administrative workloads, and slow response times remain persistent operational challenges. This study develops an Intelligent Transformer-Based One-Gate System that centralizes academic services by integrating text classification, abstractive summarization, and chatbot modules. Using a Research and Development approach, the system was built from 1,000 academic documents and service queries collected from FAQs, academic regulations, guides, and digital service archives. The corpus was cleaned, tokenized, encoded, and divided into training, validation, and testing subsets. BERT was applied for document and query classification, while BART and PEGASUS were evaluated for abstractive summarization using ROUGE metrics. The chatbot was assessed through a Likert-scale user acceptance survey. The results of this research show that the BERT classifier achieved 88% accuracy and an F1-score of 0.875, PEGASUS outperformed BART with ROUGE-1 = 0.74, ROUGE-2 = 0.66, and ROUGE-L = 0.71, and the chatbot achieved an average user satisfaction score of 82%. The main contribution of this research is an integrated transformer-based one-gate architecture that combines document routing, academic document summarization, and conversational assistance in a single service platform, offering practical value for reducing fragmented academic information services and methodological value as a reference model for higher education NLP implementation.
This study provides an AI- Based document analyzer with a question-answer system that makes use of Natural Language Processing approaches that is affordable, scalable, and suitable for business, education, and research.
Radhika Sharma, Devraj Gautam· Revolutionary Advances in Co...· 0 citations
E EduAssist, an experimental framework for evaluating a locally deployed Qwen3:1.7B model for educational document summarization, provides exploratory empirical evidence for the feasibility of local educational document summarization using the evaluated Qwen3:1.7B configuration while highlighting the need for larger datasets, model comparisons, independent reference summaries, and human evaluation.
Mohammed Afzal, Shifa Tahreem· International Journal of Eng...· 0 citations
A Retrieval-Augmented Generation (RAG)-based chatbot for academic regulation information services using a locally deployed Large Language Model (LLM) and promising feasibility for supporting document-based academic regulation information services is indicated.
It is concluded that an NLP- and RAG-based chatbot is feasible to be implemented as a digital campus information service and improves answer accuracy from 58.5% to 89.25%, with an average response time below three seconds.
Zuhri Yanda, Yeni Yanti, Maulinda et al.· IC-ITECHS· 0 citations
Artificial Intelligence (AI) is transforming academic libraries by enabling intelligent, efficient, and user-centric information services. As higher education institutions continue to embrace digital transformation, AI technologies such as machine learning, natural language processing, chatbots, recommendation systems, predictive analytics, and optical character recognition are redefining traditional library operations. AI-enabled tools, facilitate the automation of routine tasks, enhance information retrieval, improve metadata generation, support personalized learning, and provide round-the-clock virtual reference services. Consequently, AI has emerged as a strategic tool for improving operational efficiency, optimizing resource management, and enriching user experiences in academic libraries. This paper presents a conceptual analysis of the role of Artificial Intelligence in empowering academic libraries, with particular emphasis on the Indian higher education context. The study is based on an extensive review of scholarly literature, research reports, policy documents, and recent developments in AI-enabled library services. It examines the major applications of AI across library functions while critically analyzing the technological, organizational, ethical, legal, and financial challenges associated with its adoption. The study identifies key barriers, including inadequate digital infrastructure, shortage of AI-skilled library professionals, budget constraints, data privacy concerns, algorithmic bias, and resistance to organizational change. The paper also highlights the evolving role of librarians as facilitators of intelligent information services and emphasizes the need for continuous professional development and interdisciplinary collaboration. The study concludes that AI should be viewed as an enabling technology that compliments rather than replaces library professionals. Successful implementation requires strategic planning, institutional support, ethical governance, and sustained investment in infrastructure and human resource development. The study findings provide valuable insights for librarians, university administrators, policymakers, and researchers seeking to develop innovative, inclusive, and sustainable AI-driven academic library services capable of meeting the evolving information needs of the scholarly community.
D. S· Edumania-An International Mu...· 0 citations
To address the difficulty faced by university faculty and students in obtaining useful information from massive campus data, this paper proposes an intelligent campus question-and-answer (Q&A) system based on dynamic retrieval-augmented generation (RAG) technology, using campus administrative knowledge as the data source. The system integrates large language models (LLMs) with domain-specific professional knowledge, leveraging the Campus All-in-One project as a foundation. It constructs a campus knowledge base that includes administrative guides, frequently asked questions, and regulatory documents as an external data corpus. By applying the Infinity database, designed specifically for dynamic RAG applications, and employing prompt engineering, the model’s ability to generate accurate and context-aware answers is enhanced. Through this dynamic RAG-based approach tailored for the education domain, the system provides users with interactive access to a wide range of campus administrative information, helping to resolve common issues, simplify inquiry processes for teachers and students, and reduce the workload of campus management.
Charan Thumma, Abhignan Srivatsava Sribhashyam, Chaitanya Tumma et al.· 2026 International Conferenc...· 0 citations
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