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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: 2017-08-10 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 連結: http://dx.doi.org/10.3233/978-1-61499-484-8-511
    DOI: 10.3233/978-1-61499-484-8-511
    顯示於類別:[資訊科學系] 會議論文

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