Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/103258
Title: | Intelligent artificial agent for information retrieval |
Authors: | Pulis, Michael Azzopardi, Joel Micallef, Jeffrey J. |
Keywords: | Information retrieval -- Methodology Machine learning -- Technique Deep learning (Machine learning) Industries -- Databases Artificial intelligence |
Issue Date: | 2022 |
Publisher: | Springer |
Citation: | Pulis, M., Azzopardi, J., & Micallef, J. J. (2022). Intelligent Artificial Agent for Information Retrieval. In 20th International Conference on Practical Applications of Agents and Multi-Agent Systems: The PAAMS Collection, Aquila, Italy. 500-506. |
Abstract: | Throughout the day of the average employee at RS2, there will often be a need to search one of the company’s information repositories. Finding the information will often force employees to perform a context switch and search within the appropriate repository. We propose a system that will facilitate this process by creating a ChatBot that can perform the search within the company’s chat client by making use of the latest machine learning techniques, alongside several NLP techniques and established industry standard information retrieval technologies to allow for a single consolidated, optimised searching system. Results on benchmark datasets show that our system was able to achieve the best results when making use of a combination of traditional and modern techniques. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/103258 |
ISBN: | 9783031181924 |
Appears in Collections: | Scholarly Works - FacICTAI |
Files in This Item:
File | Description | Size | Format | |
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Intelligent artificial agent for information retrieval 2022.pdf Restricted Access | 796.61 kB | Adobe PDF | View/Open Request a copy |
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