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題 名 | 針對處理工作流程例外之高效率搜尋方法=High Performance Searching Algorithms for Exception Handling in Workflow |
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作 者 | 林朝興; 許正昌; | 書刊名 | 資訊管理展望 |
卷 期 | 6:1 2004.03[民93.03] |
頁 次 | 頁73-98 |
分類號 | 494.542 |
關鍵詞 | 知識管理; 工作流程; 例外處理; 工作流程管理系統; Knowledge management; Workflow; Exception handling; Workflow management system; |
語 文 | 中文(Chinese) |
中文摘要 | 隨著知識經濟的興起,建置知識管理系統來有效的管理與保存有價值的知識,就成為企業保持競爭優勢的議題。但除了知識管理外,如何縮短企業工作流程處理各種事件的時間,快速反應例外狀況並有效管理,也是企業面對競爭,所應正視之重要議題。一般而言,搜尋解決流程例外的過程,共分成兩個部分,一是各例外屬性與已知例外相似度的比對、二是依各屬性之相似度尋找最相似之例外處理。然而傳統搜尋相似度是採取循序的方法,重複的比對導致搜尋相似度非常沒有效率。本研究提出兩種比對例外屬性相似度的方法,分別是座標計算二元法(BCC, Binary Coordinate Computation)、座標計算劃分法(PCC, Partition Coordinate Computation)用以快速找出該例外屬性在其概念階層中與各例外節點之相似度。本論文我們透過演算法複雜度及模擬實驗,詳盡分析並評估BCC、 PCC與傳統循序法在不同之資料節點分佈時搜尋比對相似度的效能優劣。 |
英文摘要 | With the approaching of knowledge-based economy, in order to remain competitive, most of corporations are eager to develop knowledge management systems to effectively manage and reserve valuable knowledge. In addition to managing knowledge, how to shorten the process time of various events along workflow and also provide prompt response to exceptions is one of the major issues to be addressed while facing global competitions in a corporation. In general, the process of searching for exception handling consists of two parts; one is to compare the similarity between an exception attribute and existing exception handling; the other is to find the most similar exception handling according to the similarity of each attributes. However, traditional search for similarity is to compare exception nodes in an orderly fashion. The repeated computation results in inefficient search performance. In this research we propose two algorithms for the match with exception attributes, BCC (Binary Coordinate Computation) and PCC (Partition Coordinate Computation), to rapidly find the similarity of an attribute and each exception node in the concept hierarchy. Thorough analysis and evaluation of the pros and cons for BCC, PCC and the conventional sequential matching algorithm in the search for similarity based on the different distribution of data nodes in concept hierarchy is presented in the paper. |
本系統中英文摘要資訊取自各篇刊載內容。