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arXiv · 1502.01057

Personalized Web Search

Li Zhou
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Abstract

Personalization is important for search engines to improve user experience. Most of the existing work do pure feature engineering and extract a lot of session-style features and then train a ranking model. Here we proposed a novel way to model both long term and short term user behavior using Multi-armed bandit algorithm. Our algorithm can generalize session information across users well, and as an Explore-Exploit style algorithm, it can generalize to new urls and new users well. Experiments show that our algorithm can improve performance over the default ranking and outperforms several popular Multi-armed bandit algorithms.

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Li Zhou. 2015-02-03. Personalized Web Search. https://arxiv.org/abs/1502.01057

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