Recommender Systems for the Social Web (Intelligent Systems Reference Library)
暫譯: 社交網路的推薦系統(智慧系統參考圖書館)

José J. Pazos Pazos Arias

  • 出版商: Springer
  • 出版日期: 2014-02-22
  • 售價: $4,510
  • 貴賓價: 9.5$4,285
  • 語言: 英文
  • 頁數: 244
  • 裝訂: Paperback
  • ISBN: 3642446272
  • ISBN-13: 9783642446276
  • 相關分類: 推薦系統
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

The recommendation of products, content and services cannot be considered newly born, although its widespread application is still in full swing. While its growing success in numerous sectors, the progress of the  Social Web has revolutionized the architecture of participation and relationship in the Web, making it necessary to restate recommendation and reconciling it with Collaborative Tagging, as the popularization of authoring in the Web, and  Social Networking, as the translation of personal relationships to the Web. Precisely, the convergence of recommendation with the above Social Web pillars is what motivates this book, which has collected contributions from well-known experts in the academy and the industry to provide a broader view of the problems that Social Recommenders might face with.  If recommender systems have proven their key role in facilitating the user access to resources on the Web, when sharing resources has become social, it is natural for recommendation strategies in the Social Web era take into account the users’ point of view and the relationships among users to calculate their predictions. This book aims to help readers to discover and understand the interplay among legal issues such as privacy; technical aspects such as interoperability and scalability; and social aspects such as the influence of affinity, trust, reputation and likeness, when the goal is to offer recommendations that are truly useful to both the user and the provider.

商品描述(中文翻譯)

產品、內容和服務的推薦不能被視為新生事物,儘管其廣泛應用仍在全速進行中。隨著其在眾多領域的成功增長,社交網路的進步已經徹底改變了網路中的參與和關係架構,使得有必要重新陳述推薦並將其與協作標記(Collaborative Tagging)相調和,這是網路上創作的普及,以及社交網路(Social Networking),即將個人關係轉化為網路上的表現。正是推薦與上述社交網路支柱的融合,激發了本書的動機,本書匯集了來自學術界和業界的知名專家的貢獻,以提供對社交推薦系統(Social Recommenders)可能面臨的問題的更廣泛視角。如果推薦系統已經證明了其在促進用戶訪問網路資源中的關鍵角色,那麼當資源共享變得社交化時,社交網路時代的推薦策略自然會考慮用戶的觀點以及用戶之間的關係來計算其預測。本書旨在幫助讀者發現和理解法律問題(如隱私)、技術方面(如互操作性和可擴展性)以及社會方面(如親和力、信任、聲譽和相似性的影響)之間的相互作用,當目標是提供對用戶和提供者都真正有用的推薦時。