隨著網際網路的快速發展，許多的紙本刊物也隨著電子化，使用者能取得的資訊也日漸豐富。其中有很多的資料都是屬於定期發表且討論領域類似的期刊，更是研究人員經常閱覽的資料。目前網路上如SDOS、PubMed等的線上資料庫就是專門蒐集這些期刊並提供搜尋引擎供使用者方便搜尋想要的資料，以減少使用者在搜尋資料上的所要花費的時間與精力。然而，這些線上資料庫皆並未對每本期刊其內容的領域做更詳細的分析。對於想要投稿期刊的研究人員或想要找特定一本期刊閱讀時，並無法由期刊名完全了解其內容趨勢，必須閱讀該本期刊的數篇甚至數十篇的文章才能得知該本期刊的內容趨勢以決定此期刊是否適合投稿或選讀，所以如何幫助研究人員方便且快速的找出期刊的內容趨勢就是本研究想要探討的問題。
然而隨著時間的演進、技術的開發，期刊的內容趨勢與討論主題也會隨著改變。但是傳統的文件比對方法並未考慮時間因素，而每本期刊可能在不同時期會有不同的著力點。所以在分析中加入時間這個重要的特性，將一定時間內期刊文章的研究主題做分析，以擷取出期刊的內容趨勢，對於研究人員在期刊閱讀、資料收集與論文投稿等問題上將有所協助。因此本研究將對以定期出刊的電子期刊利用主題偵測及語意網的技術，根據期刊文章的標題、摘要及關鍵字做分類，並使用老化理論的概念考慮時間因素的變化來分析期刊的研究趨勢，進一步取出期刊在內容趨勢上的演進，提供研究人員更完善的資訊，並證明本研究所提出的方法的實驗結果較傳統方法來的優秀。

Due to the well-develop of Internet, electronical journals have become a trend. User can obtain information more and faster than before. In these, research journals database is most important resource to researchers. Online academic databases, such as SODS, PubMed, collected lot of electronical journal articles and provide their own search engine for user to search which can reduce the time expenses in searching data. However, these online databases have not analyze the publication domains contained in each journal. For the researchers who want to read or submit paper to a journal, they must read a lot of articles of that journal to figure out which one is its target. Therefore, how to help researcher to find out the target by analyzing the publish trend of a journal is the issue of this research want to discuss. Since the online databases now are only provide the function of searching data but not doing analyze to topics of journals. If we can find out the research topic of journal fast, it will improve efficiency for reading or submitting.
Moreover, the research trend and topic will change along with time and the development of technique. However, traditional document analysis method didn’t consider the time factor. If the time is taking into consideration, we can analyze journal articles’ trend. This research will use topic detection and natural language processing to analyze the research trend of journal. And further, retrieve the variation of research trend on journal according to the effect by time to provide more information for researcher in paper reading and submission. And we will prove that the result of our method is better then traditional way.

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