隨著大量資料的時代來臨，充分有效的管理知識以及對於知識的分享、重複使用與整合是非常重要的。在知識管理的範疇中，知識地圖經常被使用來協助於知識庫內知識的導引與取得，其建構的過程一般是透過屬性擷取與分群方法，接著利用資訊視覺化的技術呈現結果。資訊視覺化的技術著重在人類獨特的思考創造能力、特徵辨識能力以及對複雜圖形的迅速認知能力，以彌補電腦在自動化的過程中不具彈性的缺點，並將大量、高維度的資料利用圖形化的方式呈現，將隱含的資訊以視覺特徵呈現，透過人類與生俱來的視覺特徵辨識能力為導向，快速擷取出有用的資訊。適用於知識地圖的分群方法，需要具備將資料複雜維度簡單化與重要概念視覺化的能力，由於知識結構是階層性的架構，透過階層式方法建構的知識地圖，有助於使用者了解知識的意涵與關聯。本研究提出整合階層式技術的方法論，分群的部份，分析各群的標記名稱與專家建議的概念；視覺化的部分，整合具有描述樹狀結構的視覺化方法。最後測試階層架構的有效度與使用度，完成具有階層意涵的知識地圖。

Along with the coming of mass materialization era, the full effective knowledge management regarding the knowledge share, the repetition use and as well as conformity do count much. In knowledge management, the knowledge map is frequently used to assist knowledge guiding and obtaining. The process of knowledge forming is through feature extraction and clustering, followed by using information visualization technique to present the result. In order to atone for the weakness of non-flexibility in the process of computer automation, information visualization technique emphasizes human’s unique thinking, creativity, recognition and rapid cognition ability to complex graphs, afterward ,the massive and high dimension material would be displayed through graphing. Furthermore, the innate human visual characteristic recognition is a perfect guidance to review the hidden information for retrieving useful one. The clustering technique suitable to knowledge map must have the capability of simplifying complicated information and visualizing important concepts. Based on the fact that knowledge structure itself is a hierarchical framework, the knowledge map constructed by hierarchical visualization technique provides users with great understanding on knowledge denotation and connection. This study proposes two kinds of hierarchical techniques: clustering and visualization. The part of clustering is to analyze various groups of labels and concepts suggested by experts; as to the part of visualization, is to integrate any visualization techniques described with trees structure. Finally we testify the validity and usability of the hierarchical framework and complete the meaningful knowledge map with hierarchical information structures.

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