推送信息传递的推荐引擎
我想开发一个包含用于推送信息传递的推荐引擎的系统。我看过很多关于使用某些引擎的解释，比如 Mahout Taste 和 Duine。然而，通过使用它们，推荐的项目是在包含用户Id的输入发生后获得的。因此，此类引擎似乎仅适用于使用用户拉请求的 Web 应用程序/服务。
但是通过使用推送消息，我希望我的服务器主动向基于相关推荐算法的某些特定用户/客户直接发送推荐消息。一旦数据库中有新项目（产品/内容）可用，交付过程就会立即执行。
我的问题是，是否可以/建议使用现有的引擎，例如 Mahout 或 Duine？哪些算法可以很好地做到这一点？
I want to develop a system that involves a recommendation engine for a push information delivery. I have seen plenty of explanations about using some engines, like Mahout Taste and Duine. Yet by using them, the recommended items are obtained after an input containing user Id occurs. So, such engines seem to be suitable only for web applications/service that use pull-request from users.
But by using push messaging, i want my server to actively send a recommmendation message directly to some particular users/customers that are based on recommendation algorithm, relevant. The delivery process would be performed as soon as a new item (product/content) available in the database.
My question, is it possible/recommended to use the existing engines, like Mahout, or Duine? What algorithms are good in order to do this?
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您所做的区别是什么——无论您向用户推送还是从用户拉取，您大概都有他们的用户 ID。这并不影响推荐。无论您想推还是拉，您都可以在任何一种情况下进行推荐。
What's the distinction you're making -- whether your push to or pull from a user, you have their user ID, presumably. This doesn't affect recommendations. You can recommend in either case, whether you want to push or pull.