Integration with Modern AI Techniques for Personalized Web Search

Authors: Nitya sri Nellore

DOI: https://doi.org/10.5281/zenodo.14615481

Short DOI: https://doi.org/g8x3qb

Country: USA

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Abstract: Personalized web search (PWS) aims to improve user satisfaction by tailoring search results to individual preferences. Despite significant advancements, challenges such as user intent ambiguity, data sparsity, and privacy concerns persist. The integration of modern AI techniques, including deep learning, reinforcement learning, and natural language processing (NLP), offers promising solutions. This paper explores the application of these AI techniques in enhancing PWS, with a focus on user profiling, query disambiguation, and privacy-preserving mechanisms. Experimental results demonstrate that AI-driven models significantly improve the relevance and diversity of search results, paving the way for a new era of intelligent web search.

Keywords: -

Paper Id: 232000

Published On: 2019-02-06

Published In: Volume 7, Issue 1, January-February 2019

Cite This: Integration with Modern AI Techniques for Personalized Web Search - Nitya sri Nellore - IJIRMPS Volume 7, Issue 1, January-February 2019. DOI 10.5281/zenodo.14615481

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