Of course, an uninformed recommender is just a degenerate case and may still be useful.
当然，一个信息不足的推荐系统只是一个比较不理想的情况但可能仍然是有用的。
As such, a recommender must be able to accommodate the active participation of both the place-owner and visitor.
因此，一个推荐系统必须能够容纳积极参与其中的网站所有者和访客两方。
Perhaps the biggest issue facing recommender systems is that they need a lot of data to effectively make recommendations.
或许推荐系统面临的最大问题，是需要大量的数据，以便能形成有效的推荐。
Please see also my earlier post, "Attacking recommender systems", that discusses another paper by some of the same authors.
可以看看我更早的一篇博文：《攻击推荐系统》，讨论了来自同几个作者的一篇文章。
Notwithstanding this, interaction with a live sales agent may well be an appropriate option for a recommender to trigger in certain situations.
尽管如此，在某些情况下和现场的销售代理商进行交流，很可能是一个适当的推荐触发方式。
Online experiments providing the strongest evidence that the recommender system has a value.
在线实验可以为推荐系统的评估提供最有力的证据。
It measures the percentage of items for which the recommender system can produce recommendations.
它测量了推荐系统产生推荐项目的占比。
Some recommender systems require the user to manually enter a personal profile of interests, preferences, or expertise.
一些推荐系统需要用户手动输入一个包括个人爱好、兴趣或专长的个人信息文件。
In E-commerce recommender system, collaborative filtering technology is the most popular and successful method at present.
电子商务推荐系统中协同过滤已成为目前应用最广泛、最成功的推荐方法。
Recommender systems might be evaluated against various aspects of a recommender system, namely, functional and non-functional.
推荐系统的评估可以考虑各种不同的方面，亦即，功能性的和非功能性的。
Absrtact: In E- commerce recommender system, collaborative filtering technology is the most popular and successful method at present.
摘 要：电子商务推荐系统中协同过滤已成为目前应用最广泛、最成功的推荐方法。
Catalog coverage measures the percentage of items for which the recommender system has ever made recommendations from the total available number of items.
目录覆盖率测量的是推荐系统做出的推荐项目占全部可用项目个数的比值。
The collaborative filtering for the personalized recommendation is by far the most widely used and the most successful personalized recommender technology.
其中，个性化推荐系统中的协同过滤推荐是迄今为止应用最广泛、最成功的推荐技术。
This gives secondary effects like very fast graph algos, recommender systems and OLAP-style analytics that are currently not possible with normal RDBMS setups.
此外，Neo4j还提供了非常快的图形算法、推荐系统和OLAP风格的分析，而这一切在目前的RDBMS系统中都是无法实现的。
The evaluation in the recommender systems domain might be done utilizing several principal approaches, namely, off-line experiment, user studies and online experiments.
推荐系统可以使用的几种主要的评测方法包括离线实验，用户调研和在线实验。
Article 5 When the listed company applies for issuing new shares, the securities company qualified as main underwriter shall act as the recommender and the main underwriter.
第五条上市公司申请发行新股，应当由具有主承销商资格的证券公司担任发行推荐人和主承销商。
The goal of this approach is to filter out algorithms which have poor performance before the recommender system will be evaluated with a user study or online type evaluations.
此方法的目的在于对推荐系统执行用户调研或者在线评估之前过滤掉性能较差的算法。
Collaborative filtering is the most widely used and successful technology for personalized recommender systems. However it faces challenges of scalability and recommendation accuracy.
协同过滤是个性化推荐系统中应用最广泛和最成功的推荐技术，但是它也面临着推荐准确度和可扩展性两大挑战。
Collaborative filtering recommendation algorithm can make choices based on the opinions of other people. It is the most successful technology for building recommender systems to date.
协同过滤是目前最成功的一种推荐算法，它能够基于其他用户的观点帮助人们作出选择。
In fact, the two general factors involved in persuasion seem to be perceived expertise and trustworthiness, where the latter means whether you think the recommender has your best interests at heart.
事实上，和劝说紧密相连的2个因素通常是专业知识和可信赖性，后者意味着是否你认为这些建议是以你的利益为中心。
The experimental results show that the recommender efficiency of the proposed algorithm is obviously higher than those of traditional algorithms, and it has stronger scalability and higher utility.
实验结果表明，该算法推荐效果明显优于传统算法，具有较强的伸缩性和较高的实用价值。
Are Recommender Systems Good for Libraries?
推荐系统适用于图书馆吗？
Recommender: Interface for providing recommendations.
Recommender：用于提供推荐的界面。
Recommender System; Collaborative Filtering; User Trust; Malicious Attack; Similarity.
推荐系统；协同过滤；用户信任；恶意攻击；相似性。
Recommender System makes recommendations to user by predicting interest of the user, it helps user to filter information.
推荐系统通过预测用户的喜好对用户做出推荐，为用户进行信息过滤。
Recommender System makes recommendations to user by predicting interest of the user, it helps user to filter information.
推荐系统通过预测用户的喜好对用户做出推荐，为用户进行信息过滤。
应用推荐