Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
We introduce a new, powerful class of text proximity queries: find an instance of a given "answer type" (person, place, distance) near "selector" tokens matchi...
Large-scale cluster-based Internet services often host partitioned datasets to provide incremental scalability. The aggregation of results produced from multiple partitions is a f...
The basic aim of the model proposed here is to automatically build semantic metatext structure for texts that would allow us to search and extract discourse and semantic informati...
In dynamic environments with frequent content updates, we require online full-text search that scales to large data collections and achieves low search latency. Several recent met...