Fast First-Phase Candidate Generation for Cascading Rankers
Qi Wang, C Dimopoulos, Torsten Suel · 2016
Current search engines use very complex ranking functions based on hundreds of features. While such functions return high-quality results, they create efficiency challenges as it is too costly to fully evaluate them on all documents in the union, or even intersection, of the query terms. To address this issue, search engines use a series of cascading rankers, starting with a very simple ranking function and then applying increasingly complex and expensive ranking functions on smaller and smaller sets of candidate results. Researchers have recently started studying several problems within this framework of query processing by cascading rankers; see, e.g., [5, 13, 17, 51].