# Context Models For Web Search Personalization

arXiv: https://arxiv.org/abs/1502.00527 · HTML: https://mlsanity.com/paper/1502.00527/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Feb 2015.

## Built on by (most cited first, 1 of 1)

- [USER: A Unified Information Search and Recommendation Model based on Integrated Behavior Sequence](https://mlsanity.com/paper/2109.15012/) (2021)

## Abstract (arXiv)

We present our solution to the Yandex Personalized Web Search Challenge. The aim of this challenge was to use the historical search logs to personalize top-N document rankings for a set of test users. We used over 100 features extracted from user- and query-depended contexts to train neural net and tree-based learning-to-rank and regression models. Our final submission, which was a blend of several different models, achieved an NDCG@10 of 0.80476 and placed 4'th amongst the 194 teams winning 3'rd prize.