ItemConference Paper

Hierarchical Retrieval Augmentation Generation for Multimodalized Woman's Companion

Title
Hierarchical Retrieval Augmentation Generation for Multimodalized Woman's Companion
Creator
Sundharess, B.; Joy, Helen K.; Rajasekaran, Sridevi; Varghese, Nisha; Gobi, R.; Rajesh Kanna, R.
Description
Empowering Women in society currently face many health-related problems due to the lack of health literacy. Specifically, people are not open to talking about such as sexually transmitted diseases and mental health problems, and counselling is considered taboo in most parts of the world. Some female children grow up under the care of single fathers who are sometimes unaware of the menstrual cycle and the necessary precautions. The solution presented by the research to overcome the problem is a women's health chatbot using Large Language Models (LLM). The research proposes an enhanced retrieval augmentation generation (RAG) architecture that uses the Cloudbased API to get a faster response from the LLM. The women's health chatbot secures data privacy by not saving conversations and being available for 24 hours. Addressing various women's health concerns-such as menstrual health, mental health, pregnancy, and menopause-the chatbot employs the LangChain framework for processing and indexing health-related documents into a vector store for efficient retrieval. The chatbot also features an alert mechanism to identify critical conversations, such as those involving suicidal thoughts, and sends alerts to specified contacts. This integrated approach aims to improve access to accurate health information and support women to make informed health decisions. 2025 IEEE.
Source
Proceedings of IEEE International Conference for Women in Innovation, Technology and Entrepreneurship, ICWITE 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
component; formatting; insert; style; styling
Coverage
Sundharess B., Christ University, Department of Computer Science, Bangalore, India; Joy H.K., Christ University, Department of Computer Science, Bangalore, India; Rajasekaran S., Christ University, Department of Computer Science, Bangalore, India; Varghese N., Christ University, Department of Computer Science, Bangalore, India; Gobi R., Christ University, Department of Computer Science, Bangalore, India; Rajesh Kanna R., Christ University, Department of Computer Science, Bangalore, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 978-166545762-0;
Format
online
Language
English
Type
Conference paper

Citation

Sundharess, B.; Joy, Helen K.; Rajasekaran, Sridevi; Varghese, Nisha; Gobi, R.; Rajesh Kanna, R., “Hierarchical Retrieval Augmentation Generation for Multimodalized Woman's Companion,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/26150.

Output Formats