collaborative filtering 中文意思是什麼

collaborative filtering 解釋
共同篩選
  1. Second, proposing a hybrid recommendation strategy which used multi - agent system, collaborative filtering, and top - n together to generate right recommendations for customers in different profitability tiers. in the first part, we have defined customer value from two categories : intrinsic value and network value. based on customer ' s historical behavior, segment them with considering their recency, frequency, and monetary

    明確指出高價值客戶可體現在兩個方面：一是具有高自身價值的客戶，二是具有高網路價值（客戶的網路影響力）的客戶；其次，由顧客的歷史和當前行為，特別是從recency （最近訪問時間） 、 frequency （訪問頻度） 、 mon6t8ry （購買投人）因素出發，進行顧客內部價值挖掘：並通過形式化顧客的網路價值，給出完整的分層演算法和相應實驗。
  2. An adaptive algorithm of collaborative filtering recommender based on aggregate - neighborhood

    基於概念分層的個性化推薦演算法
  3. Design and implementation of whurecomm recommending system based on collaborative filtering

    推薦系統的設計與實現
  4. A survey of collaborative filtering algorithm applied in e - commerce recommender system

    電子商務推薦系統中的協同過濾推薦
  5. During the course of information recommending, the thesis combines content - based filtering with collaborative filtering to find particular information for each user, and it also presents different collaborative filtering strategies. in personalized information retrieval, the thesis takes advantage of the user ' s profile which describes particular user ' s information needs to filter useful information from the retrieval results for particular user and to enhance the accuracy of retrieval

    與以往系統不同，系統無需用戶直接反饋，而是通過其對文檔的訪問頻度、駐留時間及操作行為等來隱式獲取用戶的評價信息；同時，系統也利用用戶候選興趣特徵向量來記錄和累計用戶潛在的、非主要的興趣的變化過程，精度更高。
  6. In our research, firstly, we analyze the influence factors in customer buying processing. we use collaborative filtering and agent technology to anticipate the social influence and psychology tendency

    本文中我們首先分析了顧客購買過程的決策影響因素，特別是社會因素和心理因素，並將其與協作過濾和智能主體分別進行結合。
  7. A new model of user navigation prediction based on collaborative filtering

    基於本體模型的信息檢索機制研究
  8. Collaborative filtering algorithm based on rough set

    一種基於粗集的協同過濾演算法
  9. Experimental results show that this method is of low memory requirements and lower mean absolute error ( mae ) value, and provides better recommendation quality compared with traditional collaborative filtering algorithms

    實驗表明，這種方法的優點是低內存需求，具有較小的平均絕對偏差值，並且顯示出了比傳統推薦演算法更好的推薦質量。
  10. This advisory function resembles amazon ' s well - known book recommendation feature, which takes advantage of search and purchasing patterns of communities of users ? a process sometimes called collaborative filtering

    這種諮詢特性是利用使用者社群的查詢與購買模式達成，和亞馬遜知名的書籍推薦功能一樣，有時也被稱為協同篩選。
  11. Because the traditional collaborative filtering recommendation has certain insufficiency such as recommendation precision, the data processing efficiency, this article proposes a collaborative filtering method based on cluster and project forecast in coordination. after the users and the commodities are carried into gathers, the people of the same kind and the commodity of the same sort should be constructed the

    由於傳統協同過濾推薦在推薦精度、數據處理效率都有一定的不足，文中提出一種基於聚類和項目預測的協同過濾方法，把用戶、商品進行聚類后，將同屬一類的用戶、商品構建用戶? ?商品子矩陣，在該矩陣基礎上進行最近鄰查詢，從而計算用戶對未評分項目的預測評分。
  12. Worth to mention, customer ' s network value has first been used to do segmentation in the research. in the second part, we have proposed a hybrid recommendation strategy. compared with traditional ones, it has combined multi - agent system, collaborative filtering, and a simplified top - n algorithm together

    對于第二部分，其主要工作是在完成客戶分層的基礎上，本文提出了基於多智能主體和協作過濾相結合的高盈利率客戶推薦策略，通過智能主體對用戶興趣的分析，結合協作過濾中的群體意見，最終完成推薦。
  13. Research on clustering - based collaborative filtering

    基於聚類的優化協作過濾技術
  14. Collaborative filtering recommendation system based on web log and commodities classification

    日誌和商品分類的協同過濾推薦系統
  15. Aiming at some problems of collaborative filtering technologies, we have explored item - based collaborative filtering algorithm, which solves effectively sparsity and scalability problems

    針對協作過濾方法的某些缺點，提出了一種改進的過濾演算法-基於信息項的協作過濾演算法。
  16. We propose a collaborative filtering crm algorithm to mine the most possible commodity item that the customer is most favorable

    本文提出了利用協同過濾演算法來挖掘客戶最可能喜歡的商品項目的方案。
  17. Model of collaborative filtering in e - commerce recommender system based on interest measure

    基於興趣度的協同過濾商品推薦系統模型
  18. Collaborative filtering is a successful technology that is implemented in e - commerce recommender systems today

    協同過濾是目前在電子商務推薦系統中應用較為成功的個性化推薦技術。
  19. It gives emphasis to analyzing the problems which collaborative filtering is facing when it is applied in recommender systems and existing improved methods

    著重分析了協同過濾在推薦系統中應用時所面臨的問題，以及現有的解決方法。
  20. The paper introduces e - commerce recommender systems and the typical technologies that are implemented in them, collaborative filtering technology and its two directions of existing algorithms

    論文全面介紹了電子商務推薦系統及其典型的實現技術、協同過濾及已有協同過濾演算法的兩個方向。
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