本文設計一套方便簡易的模型化技術，對個人發表過的學術論文進行分析，進而分類出其專長領域所在。採用語言模型(language modeling)在資訊檢索(information retrieval)的應用，以其在統計理論的基礎作為根基，及結合近年興起web 2.0概念下的產物維基百科(Wikipedia)，利用其具有更新快速及進化的特性作為文集，在沒有任何歷史文集下單獨使用即有不錯的效果。本文並嘗試使用關鍵字作為分析的特徵，此為近數十年收錄論文時會被另外加上的項目。此技術可用於評估及核對個人於學術界之專長領域，進一步可用於專家搜尋。

In this work, we propose a convenient and easy modeling to analyze theses published by a person to determine his/her expertise. We use language modeling in information retrieval approaches with statistical theory foundations and use Wikipedia which follows the new concept of Web 2.0 with the merits of frequent updates and evolutionary character as corpus. Our experiments suggest that by using only the Wikipedia as corpus can produce satisfactory results. Besides, we propose to use keywords as a feature, which is commonly added in academic journal recent years. The proposed model can be used to evaluate and validate one's academic expertise. The proposed model can further be applied in expertise search engine.

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