Enhancing Personalized Search with AI: A Hybrid Approach Integrating Deep Learning and Cloud Computing
Journal Title: International Journal of Innovative Research in Computer Science and Technology - Year 2024, Vol 12, Issue 5
Abstract
This paper presents a novel hybrid approach for enhancing personalized search by integrating deep learning techniques with cloud computing infrastructure. The proposed system uses a multi-layer adaptive model augmented with a hierarchical monitoring network to capture user preferences and query semantics. Cloud-based architecture, used for Amazon Web Services, provides the necessary scalability and computing resources for the processing of large-scale research data. The system employs a custom middleware layer for efficient integration of the deep learning component with the distributed cloud infrastructure. An analysis of data on 100 million searches showed significant improvements in search accuracy and user satisfaction. The combined method achieves a 15% increase in Average Precision and a 12% improvement in Cost-effectiveness compared to the state-of-the-art baseline. Scalability analysis reveals the performance, maintaining sub-200ms latency for 95 percent. The system transforms the resource allocation efficiently into a non-volatile operation, demonstrating its potential for real-world deployment. This research contributes to the evolving field of AI-driven search optimization, solving problems in personal accuracy, scalability, and efficiency. The findings have implications for the design and implementation of ongoing research, providing insight into the integration of advanced machine learning with cloud resources.
Authors and Affiliations
Jiayi Wang, Tianyu Lu, Lin Li, Decheng Huang
Keywords
Related Articles
- EP ID EP749880
- DOI 10.55524/ijircst.2024.12.5.17
- Views 18
- Downloads 0
Deep Learning Approach To Face Conditioning Using Invertible Conditional Generative Adversarial Networks (ICGAN)
We propose another system for evaluating generative models by means of an ill-disposed process, in which we at the same time train two models: a generative model G that catches the information conveyance, and a discrimin...
Machine Learning Prospects: Insights for Social Media Data Mining and Analytics
Social network has increased surprising consideration in the most recent decade .Social network deals with enormous volume of composite as well as unstructured data and they are very hard to handle. Due to expanding dime...
Maximum Power Point Tracking Algorithms Under Partial Shading Condition
High and rising fuel consumption has occurred in past times. resulted in enormous growth in renewable energy generation and consumption. As economies Photovoltaic (PV) solar is becoming more popular as the world's intere...
Data Mining Techniques for Network Intrusion Detection and Prevention Systems
The main purpose of Intrusion Detection Systems(IDS) and Intrusion protection Systems(IPS) for data mining is to discover patterns of program and user activity, and determine what set of events indicate an attack. In the...
Polymer Modified Flexible Pavement and Characterization
Rutting is an essential explanation of untimely disintegration of black-top roadway asphalts. Asphalts constructed with polymer and different modifiers are showing further developed execution. The virgin black-top and ch...