Effective Keyword Search in Weighted Graphs (Extended Abstract)

被引：0

作者：

Kargar, Mehdi ^{[1
]}

Golab, Lukasz ^{[2
]}

Srivastava, Divesh ^{[3
]}

Szlichta, Jaroslaw ^{[4
]}

Zihayat, Morteza ^{[1
]}

机构：

[1] Ryerson Univ, Ted Rogers Sch Management, Toronto, ON, Canada

[2] Univ Waterloo, Waterloo, ON, Canada

[3] AT&T Chief Data Off, Atlanta, GA USA

[4] Ontario Tech Univ, Oshawa, ON, Canada

来源：

2021 IEEE 37TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2021) | 2021年

关键词：

D O I：

10.1109/ICDE51399.2021.00261

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Real graphs contain edge and node weights, representing penalty, distance or cost. We study the problem of keyword search in weighted node-labeled graphs, in which a query consists of a set of keywords and an answer is a subgraph. We consider three ranking strategies for answer subgraphs: edge weights, node weights, and a bi-objective combination of both node and edge weights. We propose and experimentally evaluate algorithms that optimize these objectives with an approximation ratio of two.

引用

页码：2350 / 2351

页数：2