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Search Symbol (Half-width) Description of Search Symbols
Space "AND" indicates the intertwining of key terms used in a search
Double Quotation Marks ("") ( " " ) Double quotation marks indicate the beginning and end of a phrase, and the search will only include terms that appear in the same order of those within the quotations. Example: "image process" : " image process "
? Indicates a variable letter. Entering two ? will indicate two variable letters, and so on. Example: "Appl?", search results will yield apple, apply… e , appl y … ( (often used to English word searches) )
* Indicates an unlimited number of variable letters to follow, from 1~n. Example: Enter "appl*", search results will yield apple, apples, apply, applied, application…(often used in English word searches) e , appl es , appl y , appl ied , appl ication … ( (often used to English word searches) )

Boolean logic combinations of key words is a skill used to expand or refine search parameters.
(1) AND (1) AND: Refines search parameters
(2) OR (2) OR: Expands search parameters (3) NOT: Excludes irrelevant parameters


DOI stands for Digital Object Identifier ( D igital O bject I dentifier ) ,
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.

Using DOI as a persistent link

To create a persistent link, add「」 「 」 before a DOI.
For instance, if the DOI of an article is 10.5297/ser.1201.002 , you can link persistently to the article by entering the following link in your browser: 10.5297/ser.1201.002
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.

Cite a document with DOI

When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.

DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI ) 。

Abstract 〈TOP〉
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Reference ( 48 ) 〈TOP〉
  1. 15.[FPS96a] U. Fayyad, G. Piatetsky-Shapiro and P. Smyth, “The KDD Process for Extracting Useful Knowledge from Volumes of Data,” Communications of the ACM, 39(11), 1996, pp.27-34.
  2. 17.[FU96] U. Fayyad, and R. Uthurusamy, “Data mining and knowledge discovery in databases,” Communications of the ACM, 39(11), 1996, pp.24-26
  3. 22.[GLW86] A. Griffith, H. C. Luckhurst, P. Willet, “Using Inter-Document Similarity Information in Document Retrieval Systems,” Journal of the American Society for Information Science, Vol.37, pp.3-11, 1986.
  4. 25.[Hil68] D. R. Hill, A Vector Clustering Technique, Mechanized Information Storage, Retrieval and Dissemination, North-Holland, Amsterdam, 1968.
  5. 26.[HK00] J. Han, and M. Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann, 2000.
Times Cited (7) 〈TOP〉
  1. 劉世琪(2007)。中文專業文件之自動叢集處理。元智大學資訊管理學系學位論文。2007。1-47。 
  2. 邱正芳(2006)。應用資料叢集原理執行非結構型文件分群— 以某資訊通報為例。元智大學資訊管理學系學位論文。2006。1-46。 
  3. 王美淳(2003)。利用共生詞彙特性發展一個二階段文件群集法。中原大學資訊管理研究所學位論文。2003。1-72。
  4. 鍾任明(2005)。運用文字探勘於日內股價漲跌趨勢預測之研究。中原大學資訊管理研究所學位論文。2005。1-78。
  5. 張敏亮(2005)。應用資料探勘於交通事故環境之關聯規則與預測。亞洲大學資訊科學與應用學系碩士班學位論文。2005。1-60。
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