Towards Recency Ranking in Web Search

In web search, recency ranking refers to ranking documents by relevance which takes freshness into account. In this paper, we propose a retrieval system which automatically detects and responds to recency sensitive queries. The system detects recency sensitive queries using a high precision classifier. The system responds to recency sensitive queries by using a machine learned ranking model trained for such queries. We use multiple recency features to provide temporal evidence which effectively represents document recency. Furthermore, we propose several training methodologies important for training recency sensitive rankers. Finally, we develop new evaluation metrics for recency sensitive queries. Our experiments demonstrate the efficacy of the proposed approaches. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval General Terms Algorithms, Experimentation Keywords Recency ranking, recency sensitive query classification, tem...

• Type: Conference
• Year: 2010
• Where: WSDM
• Authors: Anlei Dong, Yi Chang, Zhaohui Zheng, Gilad Mishne, Jing Bai, Karolina Buchner, Ruiqiang Zhang, Ciya Liao, Fernando Diaz
• Keywords: Data Mining, Recency Sensitive Queries, Sensitive Queries, Sensitive Query Classification, WSDM 2010