A graph structure-based asset retrieval system

Jia Ling Koh, Chia Jung Chiang, Seng Chih Chu, Yi Chi Huang, Shao Chun Peng, Sz Han Wang, Te Yu Liu, Hui I. Hsiao, Chien Lin, Arbee L.P. Chen

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


Retrieving assets for reuse is often a laborious, time-consuming, and difficult task because asset information cannot be effectively maintained. In this study, an asset searching technology was developed by using the graph structures and attributes. (1) The searching strategy based on graph structure primarily considers the structural relationships between assets to evaluate the similarity between asset graphs and the query. (2) The searching strategy based on attributes uses graph structures for fast retrievals, and performs string matching on the asset documents of the graph matching results to determine the degree of similarity between an asset solution and the query according to their content descriptions and attributes. To combine the matching results of both the structures and attributes, this study developed an overall similarity evaluation and ranking mechanism to search and identify the asset solutions that most similar to the query requirement. This study provides a comprehensive asset similarity evaluation method, which can improve the effectiveness of searching assets and usability of asset resources.

Original languageEnglish
Title of host publicationIntelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014
EditorsWilliam Cheng-Chung Chu, Han-Chieh Chao, Stephen Jenn-Hwa Yang
PublisherIOS Press BV
Number of pages10
ISBN (Electronic)9781614994831
Publication statusPublished - 2015
EventInternational Computer Symposium, ICS 2014 - Taichung, Taiwan
Duration: 2014 Dec 122014 Dec 14

Publication series

NameFrontiers in Artificial Intelligence and Applications
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314


OtherInternational Computer Symposium, ICS 2014


  • asset database application
  • graph search
  • information retrieval

ASJC Scopus subject areas

  • Artificial Intelligence


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