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王泰翔

王泰翔 Tai- HsiangWang

碩士論文 (2010)

知識商務之具互補性知識商品推薦研究
On Complementary Knowledge Product Recommendation for Knowledge Commerce

關鍵字 Keywords

知識商務, 知識商品, 組合, 基因演算法, 推薦
Knowledge Commerce, Knowledge Product, Combination, GA, Recommendation

摘要

由於市場環境快速變遷,企業或個人面臨的困難及挑戰倍增,遭遇的問題更是複雜且多元。知識需求若能迅速從知識市場獲取知識,以解決問題。但知識需求者通常無法從單一知識內容獲取完整所需之知識。因此知識商務將為企業帶來知識資產管理的創新思維及獲利模式。知識商品眾多,以人工方式進行知識組合、尋找和比對知識相當耗時費力,又知識商品具私有性。因此,如何以自動化的方法組合適當之知識商品,以滿足知識需求者之客製化知識之需求,為一個重要的議題。 為了滿足前述需求,本研究發展一「知識商務之具互補性知識商品推薦研究」,依據知識需求者所輸入之知識需求,轉換為知識需求本體,並與知識商品本體資料庫做搜尋比對,找出與知識需求者相關之知識商品,最後依據知識商品組合指標,建立一知識商品組合方法,並採用基因演算法以求取最適解。 藉由本研究發展之機制,以解決尋找和比對知識所耗費時間和成本,並可推薦最適知識商品組合給知識需求者作為選購之參考,以促進知識商品的交易。

Abstract

In the rapidly changing business environment, enterprises or individuals encounter more difficulties and challenges, and their encountered problems are also more complex and diverse. To sustain their competitive advantage, knowledge requirements need to be able to acquire knowledge quickly to solve their problems. Knowledge commerce (k-commerce) brings innovative thinking and profit models of knowledge assets management for enterprises. However, knowledge product is private, and search a desired knowledge product by hand form a lot of knowledge products is very time-consuming. Besides, a single knowledge product usually cannot satisfy the complex problem. Therefore, how to recommend the appropriate combination of knowledge products for satisfying customized knowledge requirement is an important issue. To overcome the above problem, this study develops a complementary knowledge product recommendation mechanism according to knowledge requesters’ requirements. At first, this study designs a structured representation model of knowledge requirement. Subsequently, this study proposes a similarity approach to match related knowledge products based on the knowledge requester’s requirement from the knowledge product ontology base. Finally, this study proposes a knowledge product combination approach using genetic algorithms to recommend the optimal combination of knowledge products according to knowledge product combination indicators. The mechanism effectively provides the desired knowledge for knowledge requester, thus facilitates successful knowledge products transactions.


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