arrow
Return

Top-Down XML Keyword Query Processing

delete2016-05-01
delete8
PRE
AI
周军锋 (Junfeng Zhou)
W
Wei Wang *
Z
Ziyang Chen *
J
Jeffrey Xu Yu *
X
Xian Tang *
Y
Yukun Li *
DOI:10.1109/TKDE.2016.2516536delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Efficiently answering XML keyword queries has attracted much research effort in the last decade. The key factors resulting in the inefficiency of existing methods are the common-ancestor-repetition (CAR) and visiting-useless-nodes (VUN) problems. To address the CAR problem, we propose a generic top-down processing strategy to answer a given keyword query w.r.t. LCA/SLCA/ELCA semantics. By top-down, we mean that we visit all common ancestor (CA) nodes in a depth-first, left-to-right order; by generic, we mean that our method is independent of the query semantics. To address the VUN problem, we propose to use child nodes, rather than descendant nodes to test the satisfiability of a node v w.r.t. the given semantics. We propose two algorithms that are based on either traditional inverted lists or our newly proposed LLists to improve the overall performance. We further propose several algorithms that are based on hash search to simplify the operation of finding CA nodes from all involved LLists. The experimental results verify the benefits of our methods according to various evaluation metrics.
Keywords:
XML
keyword search
LCA
LList
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Knowledge and Data Engineering cover
IEEE Transactions on Knowledge and Data Engineering
IF:
10.4
Papers:
6.8K
Citations:
3.2W

Organization

Y
Yanshan University
Scholars:
1.7W
Papers: 1.1W
Citations: 1.3W
T
Tianjin University of Technology
Scholars:
8.8K
Papers: 5.9K
Citations: 1.0W
C
Chinese University of Hong Kong
Scholars:
3.4W
Papers: 3.2W
Citations: 5.6W
researcher View more organizations