Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/111902
DC FieldValueLanguage
dc.contributor資訊科學系zh_Tw
dc.creator陳良弼zh_TW
dc.creatorKoh, J.-L.en_US
dc.creatorChiang, Chiajungen_US
dc.creatorChu, S.-C.en_US
dc.creatorHuang, Yichien_US
dc.creatorPeng, S.-C.en_US
dc.creatorWang, S.-H.en_US
dc.creatorLiu, T.-Y.en_US
dc.creatorHsiao, H.-I.en_US
dc.creatorLin, C.en_US
dc.creatorChen, Arbee L.P.en_US
dc.date2015en_US
dc.date.accessioned2017-08-10T07:16:43Z-
dc.date.available2017-08-10T07:16:43Z-
dc.date.issued2017-08-10T07:16:43Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/111902-
dc.description.abstractRetrieving 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. © 2015 The authors and IOS Press. All rights reserved.en_US
dc.format.extent213 bytes-
dc.format.mimetypetext/html-
dc.relationFrontiers in Artificial Intelligence and Applications, 274, 511-520en_US
dc.relationInternational Computer Symposium, ICS 2014; Taichung; Taiwan; 12 December 2014 到 14 December 2014; 代碼 111725en_US
dc.subjectGraphic methods; Intelligent control; Intelligent systems; Query processing; Content description; Database applications; Degree of similarity; Graph search; Ranking mechanisms; Searching strategy; Similarity evaluation; Structural relationship; Information retrievalen_US
dc.titleA graph structure-based asset retrieval systemen_US
dc.typeconference
dc.identifier.doi10.3233/978-1-61499-484-8-511
dc.doi.urihttp://dx.doi.org/10.3233/978-1-61499-484-8-511
item.cerifentitytypePublications-
item.grantfulltextrestricted-
item.openairetypeconference-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
Appears in Collections:會議論文
Files in This Item:
File Description SizeFormat
index.html213 BHTML2View/Open
Show simple item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.