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題名 A graph structure-based asset retrieval system
作者 陳良弼
Koh, J.-L.
Chiang, Chiajung
Chu, S.-C.
Huang, Yichi
Peng, S.-C.
Wang, S.-H.
Liu, T.-Y.
Hsiao, H.-I.
Lin, C.
Chen, Arbee L.P.
貢獻者 資訊科學系
關鍵詞 Graphic 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 retrieval
日期 2015
上傳時間 10-Aug-2017 15:16:43 (UTC+8)
摘要 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. © 2015 The authors and IOS Press. All rights reserved.
關聯 Frontiers in Artificial Intelligence and Applications, 274, 511-520
International Computer Symposium, ICS 2014; Taichung; Taiwan; 12 December 2014 到 14 December 2014; 代碼 111725
資料類型 conference
DOI http://dx.doi.org/10.3233/978-1-61499-484-8-511
dc.contributor 資訊科學系zh_Tw
dc.creator (作者) 陳良弼zh_TW
dc.creator (作者) Koh, J.-L.en_US
dc.creator (作者) Chiang, Chiajungen_US
dc.creator (作者) Chu, S.-C.en_US
dc.creator (作者) Huang, Yichien_US
dc.creator (作者) Peng, S.-C.en_US
dc.creator (作者) Wang, S.-H.en_US
dc.creator (作者) Liu, T.-Y.en_US
dc.creator (作者) Hsiao, H.-I.en_US
dc.creator (作者) Lin, C.en_US
dc.creator (作者) Chen, Arbee L.P.en_US
dc.date (日期) 2015en_US
dc.date.accessioned 10-Aug-2017 15:16:43 (UTC+8)-
dc.date.available 10-Aug-2017 15:16:43 (UTC+8)-
dc.date.issued (上傳時間) 10-Aug-2017 15:16:43 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/111902-
dc.description.abstract (摘要) 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. © 2015 The authors and IOS Press. All rights reserved.en_US
dc.format.extent 213 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Frontiers in Artificial Intelligence and Applications, 274, 511-520en_US
dc.relation (關聯) International Computer Symposium, ICS 2014; Taichung; Taiwan; 12 December 2014 到 14 December 2014; 代碼 111725en_US
dc.subject (關鍵詞) Graphic 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.title (題名) A graph structure-based asset retrieval systemen_US
dc.type (資料類型) conference
dc.identifier.doi (DOI) 10.3233/978-1-61499-484-8-511
dc.doi.uri (DOI) http://dx.doi.org/10.3233/978-1-61499-484-8-511