Optimal Top-k,m Queries Processing: Algorithms And Applications
Lecturer: Jiaheng Lu
Lecture Time: May 24th 4:00PM
Lecture Place: Information Building, Room 417
In this talk, I will first introduce three research topics I am doing currently: XML data management, Similarity search and cloud data management. Then I will introduce our new work: top-k,m query processing. Suppose we are given a set of groups where each attribute in one group is associated with a list whose tuples are equipped with IDs and scores. The goal is to return the top-k combinations of attributes with the highest overall scores from the respective top-m scores from lists. Top-k,m queries are different from regular top-k queries in nature and useful in various emerging scenarios, including recommendation systems, query refinement and medical data mining.