A survey: Information search time optimization based on RAG (Retrieval Augmentation Generation) chatbot
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866908761198690304 |
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| author | Patel, Jinesh Malhotra, Arpit Pande, Ajay Caire, Prateek |
| author_facet | Patel, Jinesh Malhotra, Arpit Pande, Ajay Caire, Prateek |
| contents | Retrieval-Augmented Generation (RAG) based chatbots are not only useful for information retrieval through questionanswering but also for making complex decisions based on injected private data.we present a survey on how much search time can be saved when retrieving complex information within an organization called "X Systems"(a stealth mode company) by using a RAG-based chatbot compared to traditional search methods. We compare the information retrieval time using standard search techniques versus the RAG-based chatbot for the same queries. Our results conclude that RAG-based chatbots not only save time in information retrieval but also optimize the search process effectively. This survey was conducted with a sample of 105 employees across departments, average time spending on information retrieval per query was taken as metric. Comparison shows us, there are average 80-95% improvement on search when use RAG based chatbot than using standard search. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_07838 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A survey: Information search time optimization based on RAG (Retrieval Augmentation Generation) chatbot Patel, Jinesh Malhotra, Arpit Pande, Ajay Caire, Prateek Information Retrieval Artificial Intelligence Retrieval-Augmented Generation (RAG) based chatbots are not only useful for information retrieval through questionanswering but also for making complex decisions based on injected private data.we present a survey on how much search time can be saved when retrieving complex information within an organization called "X Systems"(a stealth mode company) by using a RAG-based chatbot compared to traditional search methods. We compare the information retrieval time using standard search techniques versus the RAG-based chatbot for the same queries. Our results conclude that RAG-based chatbots not only save time in information retrieval but also optimize the search process effectively. This survey was conducted with a sample of 105 employees across departments, average time spending on information retrieval per query was taken as metric. Comparison shows us, there are average 80-95% improvement on search when use RAG based chatbot than using standard search. |
| title | A survey: Information search time optimization based on RAG (Retrieval Augmentation Generation) chatbot |
| topic | Information Retrieval Artificial Intelligence |
| url | https://arxiv.org/abs/2601.07838 |