網路百科上社群知識之導航推薦機制

Abstract

在現今的世界中，知識是個人和企業用來創造核心競爭力最重要的資源，而近年來，Web 2.0和社會媒體提供了一個讓人們可以在網路上分享他們的個人知識的便利環境，但是，這樣便於分享的環境也創造出了大量的非結構化資料，並導致的資訊過載的問題。 本研究提出了一個社會知識導航系統，利用相關性知識網路建構模組、知識重要性分析模組以及知識概念本體構建模組，來產生視覺化的知識地圖及知識流的推薦，希望能藉此幫助利用線上百科全書平台來學習新知識的人。本研究的實驗結果顯示社會知識導航系統是可以推薦出現上百科全書平台上，和學習目標相關的文章，並且可以藉由本系統來提升使用者在線上百科全書的平台學習的效能。

In today’s world, knowledge is the most important resource to create core competitive advantages for individual and organization and recently, Web 2.0 applications and social media provide a convenient medium for people to share their personal knowledge over the Internet. However, the created huge amount of knowledge article resource also leads to information overload problem. This research proposes a social knowledge navigation system which utilizes the relevant knowledge network construction module, knowledge importance analysis module, and knowledge concept ontology construction module, to generate visualized recommendation of article reading sequence and knowledge map of sub-concept for supporting the learning of knowledge seekers on the free online encyclopedia. The experimental results show that the proposed mechanism can effectively recommend the useful articles and improve knowledge seeker’s learning effectiveness.