%0 Journal Article
%T 專論／分類不一致之自動偵測：以農資中心資料為例／曾元顯；王峻禧 | Automatic Inconsistency Detection for the ASIC Categorization Collection / Yuen-Hsien Tseng; Chun-Shi Wang
%A 曾元顯、王峻禧 　
%J Journal of Library and Information Science
%D 2007
%I National Taiwan Normal University
%X 文件分類是根據文件內容的主題給定類別的知識加值工作，傳統上由人工進行。然而受分類架構設計、類別定義以及分類者學識 背景等影響，主題內容類似的文件，不見得都會被分類到相同的類別，因而造成分類不一致的情況，降低分類文件的應用價值。本文以案例的形式，根據農資中心的 人工分類資料， 進行分類一致性的自動驗證，呈現及探討其結果，並說明其可能潛在的應用，以展示此項工作的可行性及實際效益。綜合而言，分類不一致之自動偵測，可作為資料 清理、知識盤點等知識管理實務上的應用，或是後續分類槃構修正、分類策略擬定、人工分類訓練，以及引進自動分類機制之參考與前置作業。 Text categorization is a process of assigning labels to documents according to the contents or topics of the documents. Traditionally text categorization is carried out by human experts. However, due to factors such as blurred category boundaries, background bias, and personal judgment, label inconsistency is often found in human classified collections, thus reducing their values in various applications. This article described an automatic process to detect such inconsistency based on the Agricultural Science Information Center (ASIC ) collection. In the article, important examples and results are presented. Potential benefits and applications are discussed. 頁次：19-32
%U http://jlis.glis.ntnu.edu.tw/ojs/index.php/jlis/article/view/495