{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"06dd97ec-cce5-45df-9acf-40e36f07dab3","title":"[数字经济前沿]技术封建主义","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787300328508","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"06dd97ec-cce5-45df-9acf-40e36f07dab3","id":"06dd97ec-cce5-45df-9acf-40e36f07dab3","uuid":"06dd97ec-cce5-45df-9acf-40e36f07dab3","title":"[数字经济前沿]技术封建主义","normalized_title":"数字经济前沿技术封建主义","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787300328508","isbns":["9787300328508"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":259,"navigation_url":"https://workshop.closeclaw.top/ai/book/06dd97ec-cce5-45df-9acf-40e36f07dab3","title_url":"https://workshop.closeclaw.top/ai/title/%5B%E6%95%B0%E5%AD%97%E7%BB%8F%E6%B5%8E%E5%89%8D%E6%B2%BF%5D%E6%8A%80%E6%9C%AF%E5%B0%81%E5%BB%BA%E4%B8%BB%E4%B9%89","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/06dd97ec-cce5-45df-9acf-40e36f07dab3/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/06dd97ec-cce5-45df-9acf-40e36f07dab3/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/06dd97ec-cce5-45df-9acf-40e36f07dab3","page_url":"https://workshop.closeclaw.top/api/ai/books/06dd97ec-cce5-45df-9acf-40e36f07dab3/page","search_url":"https://workshop.closeclaw.top/api/ai/books/06dd97ec-cce5-45df-9acf-40e36f07dab3/search"},"page":{"printed_page":91,"pdf_page":131,"physical_index":131,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"14581d05453ca4a265d4bed4c86683cd29755f85a15f0c7345796b765e086293"},"chapter":"第二章","content":"新积累逻辑的本质是对哈耶克和凯恩斯关注点的颠覆。核心不再是不确定性或不可知性，而是可预测性。祖博夫将监视资本家的战略视为一场“提高确定性程度的竞赛”，在这场竞赛中，他们别无选择，只能加强对社会活动的控制。亚马逊、谷歌和脸书正以各自的方式加强监控扩张与价值创造之间的重要联系。\n\n亚马逊与推荐逻辑。亚马逊成功的秘诀之一在于它的推荐系统及其在销售环境个性化方面的优势：\n\n亚马逊网站为每位客户量身打造了一家商店。每个来到亚马逊网站的人看到的网站都不一样，因为网站是根据他们的兴趣个性化设计的。这就好比你走进一家商店，货架开始重新排列，你想买的东西被突出显示，反之，你不可能感兴趣的东西则被排在后面。亚马逊网站的推荐系统会根据当前语境和你过去的行为，选择你或许感兴趣的少量商品。①\n\n这种个性化体验来自协同过滤算法，这种算法借鉴了其他用户的经验。不过，亚马逊发明的系统并不是将客户与其他具有相似特征的客户进行匹配，而是以物品为基础进行组织。用\n\n第二章 数字统治\n\n① Brent SMITH et Greg LINDEN, «Two decades of recommender systems at Amazon. com», IEEE Internet Com puting, vol. 21, n° 3, 2017, p. 12.\n\n091","previous_page":90,"next_page":92}