Today's query processing engines do not take advantage of the multiple occurrences of a relation in a query to improve performance. Instead, each instance is treated as a dis...
Yu Cao, Gopal C. Das, Chee Yong Chan, Kian-Lee Tan
We consider the problem of optimizing and executing multiple continuous queries, where each query is a conjunction of filters and each filter may occur in multiple queries. When f...
Kamesh Munagala, Utkarsh Srivastava, Jennifer Wido...
Previous research into the efficiency of text retrieval systems has dealt primarily with methods that consider inverted lists in sequence; these methods are known as term-at-a-tim...
In this paper, we design and evaluate alternative selection placement strategies for optimizing a very large number of continuous queries in an Internet environment. Two grouping ...
Jianjun Chen, David J. DeWitt, Jeffrey F. Naughton
Abstract--Multiple instance learning (MIL) is a recently researched technique used for learning a target concept in the presence of noise. Previously, a random set framework for mu...