Improving recency ranking using twitter data

In Web search and vertical search, recency ranking refers to retrieving and ranking documents by both relevance and freshness. As impoverished in-links and click information is the the biggest challenge for recency ranking, we advocate the use of Twitter data to address the challenge in this article. We propose a method to utilize Twitter TinyURL to detect fresh and high-quality documents, and leverage Twitter data to generate novel and effective features for ranking. The empirical experiments demonstrate that the proposed approach effectively improves a commercial search engine for both Web search ranking and tweet vertical ranking.

Authors

• Yi Chang Jilin University Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, Ministry of Education, China
• Anlei Dong Yahoo Labs
• Pranam Kolari Akshay Java
• Ruiqiang Zhang Yahoo! Labs
• Yoshiyuki Inagaki Yahoo Labs
• Fernanodo Diaz
• Hongyuan Zha Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong, Shenzhen
• Yan Liu

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