Incorporating Automated Machine Learning and Neural Architecture Searches to Build a Better Enterprise Search Engine
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V4I4P108Keywords:
Enterprise Search Engine, Automated Machine Learning, Neural Architecture Search, AI Optimization, Search Efficiency, Personalized Search Results, AI-driven Search, Machine Learning Models, Neural Networks, Dynamic Search, Search Algorithms, AutoML, Search Performance, Optimization Techniques, AI-powered Search, Custom Search Solutions, Intelligent Search, Search Technology, Smart Search, Personalized User Experience, Search EnhancementAbstract
The enterprise search engine domain has been trying to find a solution for a long time that can not only deliver the most relevant results but also be efficient in light of the steep increase in the volume of data and the change in user expectations. Models based on traditional search engines are often insufficient to deliver the level of personalization, accuracy, and speed that modern businesses require. Seeking to change the situation, the AI arena developed the Automated Machine Learning (AutoML) and Neural Architecture Search (NAS) fields that are more capable of revolutionizing the search engine game. The technologies that allow the design and upgrade of search engines in a different and better way become the dream of the future. AutoML facilitates model selection and training implementation by automatically choosing the best algorithms for the task. At the same time, NAS deals with the process of automation in finding the most suitable architectures of neural networks. This unification is potentially the key to developing more cost-effective search systems due to the increased capability of personalizing the results. AutoML equips search engines with better agility in reaction to the change of the data model and user behavior, while NAS focuses on the optimization of the neural networks for the execution of better tasks. The union of the two technologies makes way for more scalable, efficient, and dynamic enterprise search solutions
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