查詢結果分析
相關文獻
- A Hybrid Approach for Knowledge Recommendation
- The Genetic Algorithm with Rough Set Theory Incorporated into the Patent Composition
- 應用分群技術與基因演算法建構以趨勢為基礎之股市投資策略
- 應用約略集合理論於醫療機構商業流程之委外供應商評選
- Product Bundling in the Electronic Commerce Environment: A Hybrid Approach
- 運用約略集合理論建構特殊軍品管理知識庫
- 都市計畫草圖替選方案分析模式之實例研究
- 運用類神經網路於股價指數之套利--以日經225指數為例
- 二次元靜態連續體結構之最佳化:應用族群概念之基因演算法
- 遺傳基因演算法在彈性製造系統排程問題之探討
頁籤選單縮合
| 題 名 | A Hybrid Approach for Knowledge Recommendation=一個混合式的知識推薦方法 |
|---|---|
| 作 者 | 梁文耀; 黃俊哲; 潘郁婷; | 書刊名 | International Journal of Information and Management Sciences |
| 卷 期 | 27:1 2016.03[民105.03] |
| 頁 次 | 頁a7+17-39 |
| 分類號 | 494 |
| 關鍵詞 | 知識推薦; 分群技術; 約略集合理論; 基因演算法; Knowledge recommendation; Clustering techniques; Rough set theory; Genetic algorithm; |
| 語 文 | 英文(English) |
| 英文摘要 | Knowledge sharing is critical to knowledge management as it enables employees to share their knowledge. However, knowledge searching is a very time-consuming work. Additionally, in the context of an unsolved puzzle or unknown task, users typically have to determine the knowledge for which they will search. Therefore, knowledge management platforms for enterprises should have knowledge recommendation functionality. Hybrid recommendation systems (RS) have been developed to overcome, or at least to mitigate, the limitations of collaborative filtering. Because Genetic Algorithm (GA) is good at searching, it can cluster data according to similarities. However, the increase in the amount of data and information reduces the performance of a GA, thereby increasing cost of finding a solution. This work applies a novel method for incorporating a GA and rough set theory into clustering. In this paper, this work presents a hybrid knowledge recommendation model, which has a two-phase model for clustering and recommending. Approach implementation is demonstrated, as are its effectiveness and efficiency. |
本系統中英文摘要資訊取自各篇刊載內容。