Retrieval-Augmented Generation (RAG)
Генерация с дополнением извлечённой информацией (RAG)
2025-06-01
SCID: 54.1/aknqvsv3
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Enterprise search systemsInformation retrievalInformation systemsRetrieval-augmented generationUser interfaces
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Abstract (AI)
The necessity for information is a fundamental aspect of human nature, and as such, there are ongoing efforts to enhance information retrieval with information systems (Alavi and Leidner 2001 ; Alavi et al. 2024 ). Companies are particularly affected by this, as they have extensive data at their disposal, and employees need to access it. Unfortunately, current systems are not able to adequately meet employees’ expectations. In fact, studies have shown that 79% of employees are dissatisfied with the user interfaces of enterprise search systems (Cleverley and Burnett 2019 ). This has led to a need for new approaches that can better address the information needs of organizations.
Key Findings
1
Existing enterprise search systems inadequately meet employee expectations; 79% of employees report dissatisfaction with their user interfaces.
2
Information retrieval is a fundamental human need, creating continued demand for improved information systems.
3
Organizations possess extensive data, but employees often struggle to access relevant internal information effectively.
4
The abstract identifies a need for new information-retrieval approaches better suited to organizational information needs.
Research Object
enterprise information retrieval systems
Research Subject
their ability to meet employees’ information needs and expectations
Publication Details
Publication Date
2025-06-01
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References available in scid.ai4
Dense Passage Retrieval for Open-Domain Question Answering2020
Retrieval-Augmented Generation for Large Language Models: A Survey2023
Augmenting large language models with chemistry tools2024
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions2024