Relevance Estimation with Multiple Information Sources on Search Engine Result Pages

@article{Zhang2018RelevanceEW,
  title={Relevance Estimation with Multiple Information Sources on Search Engine Result Pages},
  author={Junqi Zhang and Yiqun Liu and Shaoping Ma and Qi Tian},
  journal={Proceedings of the 27th ACM International Conference on Information and Knowledge Management},
  year={2018}
}
  • Junqi Zhang, Yiqun Liu, Qi Tian
  • Published 17 October 2018
  • Computer Science
  • Proceedings of the 27th ACM International Conference on Information and Knowledge Management
Relevance estimation is among the most important tasks in the ranking of search results because most search engines follow the Probability Ranking Principle. Current relevance estimation methodologies mainly concentrate on text matching between the query and Web documents, link analysis and user behavior models. However, users judge the relevance of search results directly from Search Engine Result Pages (SERPs), which provide valuable signals for reranking. Morden search engines aggregate… 

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