學術資料擷取，整合及推薦

隨著電腦及網絡科技的進步，網路提供越來越多學術資料的服務，研究者需要搜尋相關的論文並且消化，往往會花費許多時間，本論文針對學術論文開發一套資料擷取、整合及推薦的輔助系統，讓研究者可依照自己感興趣的作者、論文或刊物，從開放的學術目錄網站取得論文資訊，並建立個人專屬的學術資料倉儲。在使用這套系統的過程中，研究者對於作者、論文及刊物的存取頻率都會分別被記錄，藉以評估其個人偏好，在另一方面，分析協同作者關係及論文引用關係，則可衡量資料倉儲內作者、論文或刊物的重要程度，結合兩者可推導一份適合推薦給研究者的資料清單。我們實作這整套系統，測量其執行效率，並蒐集真實研究者對於所推薦資料的滿意度，結果顯示本系統可以幫助研究者縮短文獻調查的時間，並且得到滿意的結果。

關鍵字

資料檢索；資料整合；個人化推薦；學術資料

並列摘要

With the advance of computer and network technology, more and more academic data and services are available on the Internet. Researchers often need to search the related articles and then digest them. There tasks can be time-consuming. This thesis develops a system for academic articles to aid the retrieval, integration and recommendation of data. It allows the researcher to acquire information from open academic catalogue website and build a personalized data repository according to their special interests in authors, articles or publications. The system would trace the frequencies about how often the researcher accesses particular authors, articles and publications, respectively, in order to assess his/her preference. On the other hand, the importance degree of authors, articles and publications in the data repository can be estimated by analyzing co-author relationships and citation relationships. Combining both can derive a list of data as the proper recommendation to the researcher. We implement the whole system, measure its execution efficiency, and gather the satisfaction levels of actual researchers towards recommended data. The results show that the system helps researcher reduce the time on doing the literature survey and obtain satisfactory results.

並列關鍵字

data retrieval ； data integration ； personalized recommendation ； academic data

參考文獻

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國際替代計量

學術資料擷取，整合及推薦

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