以工作觀為基礎之知識支援模式與系統:工作相關知識遞送與分享

Abstract

建構知識管理系統已是企業組織有效管理企業知識，獲取產業競爭優勢的重要策略。而企業主要是以工作為基礎來進行企業活動之運作與管理，組織人員執行各項工作以達成企業之營運目標。在以工作為基礎之企業環境，考量組織工作特性，設計適合的知識推薦機制，以提供組織人員工作相關之知識物件與資訊，是建構知識管理系統之重要議題。 一般而言，在各類知識物件中，文件為將知識外顯化的重要方式之一；此外，文件除提供豐富之資訊並且也是增加速度最為可觀之知識物件。因此，企業若能將各式知識物件以結構化方式存放至知識庫並使之外顯化，勢必能有效保存與提供組織知識資產。本研究主要設計以工作為基礎的主題分類架構(task domain ontology)…，並引入模糊分類方法，將企業內的各項知識物件與工作，配合該主題分類架構加以分類與整理。此外，為支援知識工作者克服執行工作中所遭遇之困難，本研究提出以工作為基礎之知識支援模式，預期達到有效知識彙集、遞送與分享之目的。 本研究首先提出系統化的工作相關知識評估機制，透過工作者間之協同合作以支援其資訊需求，並整合工作相關知識評估機制於知識支援系統中，以協助組織人員透過工作特徵檔擷取工作所需的知識。該工作相關評估機制，分析工作與知識物件之相關性並建置工作特徵檔(task profile)，以協助組織人員透過工作特徵檔擷取工作所需的知識物件，預期協助知識工作者從大量知識物件中有效獲取工作相關知識，克服工作執行中所遭遇之困難。在此基礎之上，我們更藉由知識工作者資訊回饋過程，提出修正工作特徵檔之方法外，依該工作特徵檔，提出工作社群網路分析與建構方法，並探討與評估知識工作者之間互動所構成的社群網路如何促成知識遞送與分享。研究內容主要包括：(1)提出適性化的工作特徵模式，藉由工作相關回饋機制修正工作特徵檔，以描述知識工作者之動態性工作資訊需求；(2)提出工作同好群組分析法，依據工作者特徵檔分析知識工作者資訊需求之相似性，並建立工作社群網路。在我們後續的研究中，發現工作者對於知識密集性工作之資訊需求是動態的，會隨著時間與環境而演化改變。因此，有效之知識支援需提供適性化機制以依據工作者之動態需求提供相關知識；此外，工作之執行，常需逐步執行階段性任務以完成工作，而不同階段有不同之工作資訊需求。根據組織工作特性而由系統主動提供工作相關知識的相關研究並未考慮工作之階段性；因此，本研究進一步改良先前知識支援模式，提出工作階段性為基礎之工作相關知識支援模式與系統架構。研究內容主要包括：（1）根據知識工作者不同時間點的工作特徵檔，運用相關係數分析法，偵測工作者目前之工作階段；(2)以組織之工作主題分類架構為基礎，分析知識工作者於工作執行中之主題變換情形，以判別知識工作者現階段資訊需求主題；(3)該模式依據作者之工作階段與需求主題之變換，進而調整其資訊需求特徵檔，提供符合工作階段性之相關知識。 本文並依所設計之知識支援模式而設計實驗，以驗證方法於提供知識支援之有效性。此外，並以物件導向方式實作以工作為基礎之知識支援系統，建構協同合作之工作環境，以提供有效的工作相關知識遞送與分享。該系統落實在一研究單位，藉由使用者滿意度回饋以評估系統之有效性。研究結果顯示該知識支援模式與系統能有效達成知識遞送並促進組織成員之知識分享。

In task-based business environments, a pertinent issue in deploying knowledge management system (KMS) is providing task-relevant information (codified knowledge) to fulfill the information needs of knowledge workers. Historical codified knowledge, i.e. experiences and know-how extracted from previous task executions, provides valuable knowledge for knowledge workers to accomplish tasks successfully. Accordingly, a repository of structured and explicit knowledge, especially in document form, is a widely adopted codification-based strategy for managing knowledge in KMS. This work first discusses the issue of managing codified knowledge by building the task-oriented repository from the perspective of business task. To organize and manage task-relevant information, the repository is constructed with support from domain ontology (topic taxonomy) to effectively utilize codified knowledge. Thus, providing effective knowledge retrieval function to mitigate the difficulty of accessing knowledge items from the knowledge repository is a challenging work. Accordingly, a task-based knowledge support model is proposed to tackle the problem. The proposed model proactively delivers task-relevant codified knowledge and promotes knowledge sharing among knowledge workers in task-based business environments. A novel task-relevance assessment approach is proposed to identify the knowledge worker’s information needs on tasks, for brevity, task-needs. The proposed approach generates task profiles via the collaboration of knowledge workers to analyze the relevance of tasks and codified knowledge. The approach can alleviate the problem of accessing needed knowledge items from vast amounts of codified knowledge. Moreover, an adaptive task-based profiling approach and a task peer-group analytical method are proposed to track workers’ dynamic task-needs and identify workers’ task-based peer-groups p. Knowledge workers can obtain task-relevant knowledge with the aid of task-based profiles and peer-groups. Furthermore, we seek to extend and refine our model to resolve long-term knowledge support problem. According to our empirical investigation, knowledge workers engaged in knowledge intensive task usually have different information needs during the long-term task performance. That is, another challenge of deploying KMS is to support task-relevant knowledge based on workers’ task-needs at different task progress, i.e., stages or milestones. Accordingly, we proposed a task-stage knowledge support model that incorporates the information-filtering model with the identification of worker’s task-stage. A correlation analysis method is proposed to identify a worker’s task-stage, and an ontology-based topic discovery method is proposed to determine a worker’s task-needs for specific topics of stage. Consequently, the system can be tailored to support long-term task performance. A task-based K-Support portal is developed to facilitate knowledge reuse and further to streamline task execution. The portal is grounded in a research institute to support the execution of knowledge-intensive task by stimulating the operation of knowledge delivering and sharing. Moreover, various experiments have been conducted to evaluate the proposed model. The experimental results reveal that the proposed model and system can provides knowledge support in task-based environments effectively.