Keyword search on temporal graphs

Ziyang Liu, Chong Wang, Yi Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Archiving graph data over history is demanded in many applications, such as social network and bibliographies. Typically, people are interested in querying temporal graphs. Existing keyword search approaches for graph-structured data are insufficient for querying temporal graphs. This paper initiates the study of supporting keyword-based queries on temporal graphs. We propose a search syntax that is an extension of keyword search, which allows casual users to easily search temporal graphs with temporal predicates and ranking functions. To generate results efficiently, we propose a best path iterator, which finds the 'best' paths between two data nodes in each snapshot regarding to three ranking factors. We develop algorithms that efficiently generate top-k query results. Extensive experiments verified the efficiency and effectiveness of our approach.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1807-1808
Number of pages2
ISBN (Electronic)9781538655207
DOIs
StatePublished - Oct 24 2018
Event34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France
Duration: Apr 16 2018Apr 19 2018

Publication series

NameProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018

Other

Other34th IEEE International Conference on Data Engineering, ICDE 2018
CountryFrance
CityParis
Period4/16/184/19/18

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Information Systems and Management
  • Hardware and Architecture

Keywords

  • Algorithm
  • Graph theory
  • Information retrieval
  • Keyword search

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