資訊管理學報
陳良駒;張正宏;陳日鑫;
頁: 31-60
日期: 2010/10
摘要: 議題的「結構」與「趨勢」是主題領域研究中兩項重要的探討重點，議題結構彰顯領域知識的範疇分類與相關性，議題趨勢則呈現領域知識的變化演進與時代差異。隨著知識經濟時代的來臨，「知識管理」已經成為學術界及企業實務界逐漸重視的關鍵領域。 共詞分析目的在建構領域關鍵知識的連結性，藉由詞頻的統計與詞彙的共現關係，呈現出領域知識的群集結構及演進趨勢。相關學者已使用共詞分析進行各個學域的研究，進而發掘該領域的熱門議題與發展焦點。而關聯法則分析是資料探勘技術最常被使用的方法，藉由支持度與信心水準兩個指標找出資料集合中某些項目間的關聯性；由於關聯法則的表現明確易懂，因此被廣泛的運用於不同的領域（如商業、網路及醫學等），然而卻較少於主題領域（例如：知識管理）研究議題中進行探討。 本論文即企圖使用共詞分析與關聯法則共同探討國內知識管理研究議題的結構特性與發展趨勢。藉由共詞分析中的詞頻統計、群集分析及策略座標圖來呈現知識管理的熱門研究議題與趨向；而透過關聯法則所產生出來規則，則可呈現知識管理主題領域的關聯性。
關鍵字: 知識管理;關聯法則;共詞分析;集群分析;策略座標圖;
Abstract: Issues about the ”structure” and ”tendency” are two essential points in the studies of topic domain. The former shows the classification and association of issues and the latter reveals the changes, evolution, and differences of related issues in a specific knowledge domain. With the advent of the era of knowledge economy, knowledge management (KM) has become gradually important for the academic and corporate sectors. The purpose of co-word analysis is to construct the relationship among key issues which represent the clustering or tendency of topic domain through frequency statistic and link analysis of words. Many scholars have used the co-word analysis to conduct a variety of studies for exploring the hot topics and development trends of topic domain. Besides, the association rule (AR) is a frequency-cited method for mining web content and database. AR is used to discovery the hidden associations of itemsets through two key indices (support and confidence) and it has been applied to a variety of research domains such as business, network, and medical science. However, little research focuses on the exploration of a specific topic domain (e.g. KM). The goal of this study is to explore the characteristics of keyword in a KM field with the co-word analysis and AR method. The hot topics and development trends of KM are examined by using frequency statistics, clustering analysis, and strategic diagram (i.e. co-word analysis) and the connection of related issues in KM are represented with the analysis of association rule. Both are effective for constructing the structure and tendency of topic domain.
Keywords: knowledge management;association rule;co-word analysis;clustering analysis;strategic diagram;
瀏覽次數: 12607 下載次數: 526
引用 導入Endnote
頁: 31-60
日期: 2010/10
摘要: 議題的「結構」與「趨勢」是主題領域研究中兩項重要的探討重點，議題結構彰顯領域知識的範疇分類與相關性，議題趨勢則呈現領域知識的變化演進與時代差異。隨著知識經濟時代的來臨，「知識管理」已經成為學術界及企業實務界逐漸重視的關鍵領域。 共詞分析目的在建構領域關鍵知識的連結性，藉由詞頻的統計與詞彙的共現關係，呈現出領域知識的群集結構及演進趨勢。相關學者已使用共詞分析進行各個學域的研究，進而發掘該領域的熱門議題與發展焦點。而關聯法則分析是資料探勘技術最常被使用的方法，藉由支持度與信心水準兩個指標找出資料集合中某些項目間的關聯性；由於關聯法則的表現明確易懂，因此被廣泛的運用於不同的領域（如商業、網路及醫學等），然而卻較少於主題領域（例如：知識管理）研究議題中進行探討。 本論文即企圖使用共詞分析與關聯法則共同探討國內知識管理研究議題的結構特性與發展趨勢。藉由共詞分析中的詞頻統計、群集分析及策略座標圖來呈現知識管理的熱門研究議題與趨向；而透過關聯法則所產生出來規則，則可呈現知識管理主題領域的關聯性。
關鍵字: 知識管理;關聯法則;共詞分析;集群分析;策略座標圖;
Exploring the Correlation of Knowledge Management Issues Based on co-occurrence Analysis of keywords-using the co-word and Association Rule Analysis
Abstract: Issues about the ”structure” and ”tendency” are two essential points in the studies of topic domain. The former shows the classification and association of issues and the latter reveals the changes, evolution, and differences of related issues in a specific knowledge domain. With the advent of the era of knowledge economy, knowledge management (KM) has become gradually important for the academic and corporate sectors. The purpose of co-word analysis is to construct the relationship among key issues which represent the clustering or tendency of topic domain through frequency statistic and link analysis of words. Many scholars have used the co-word analysis to conduct a variety of studies for exploring the hot topics and development trends of topic domain. Besides, the association rule (AR) is a frequency-cited method for mining web content and database. AR is used to discovery the hidden associations of itemsets through two key indices (support and confidence) and it has been applied to a variety of research domains such as business, network, and medical science. However, little research focuses on the exploration of a specific topic domain (e.g. KM). The goal of this study is to explore the characteristics of keyword in a KM field with the co-word analysis and AR method. The hot topics and development trends of KM are examined by using frequency statistics, clustering analysis, and strategic diagram (i.e. co-word analysis) and the connection of related issues in KM are represented with the analysis of association rule. Both are effective for constructing the structure and tendency of topic domain.
Keywords: knowledge management;association rule;co-word analysis;clustering analysis;strategic diagram;
瀏覽次數: 12607 下載次數: 526
引用 導入Endnote