recommend

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recommend someone as something

to suggest someone as something. Could you recommend Frank as a good carpenter? I can recommend Jane Smith as a good artist.
See also: recommend

recommend someone for something

to suggest someone for something. I would be very glad to recommend you for promotion. She recommended herself as the best choice.
See also: recommend

recommend someone or something to someone

to suggest that someone choose someone or something. I would like to recommend Sally to you as a good prospect for membership on the committee. Could you recommend a good mechanic to me?
See also: recommend
References in periodicals archive ?
Unlike recommendations in other domains, recommender systems in e-learning domain should assist learners in constructing their knowledge in a contextualized progressive way rather than acquiring it.
As per details here on Sunday, the central component of the system is an intelligent, adaptive software-based recommender system that can learn, both off-line and online, the preferences, shopping behavior, geographic attributes and demographics of the customer base.
Using tags and latent factors in a food recommender system," in Proc.
Dietmar Jannach, Tutorial: Recommender Systems, in International Joint Conference on Artificial Intelligenc eBeijing, August 4, 2013.
For ease of exposition, we first classify the social relation-ships for recommender systems into two categories, namely trust and trust-alike, and then depict their similarities and differences.
One could assume that technical improvements to recommenders would allow forecasters to issue more recommender-based polygons exactly as created; however, this outcome may not be completely desirable from a decision-making perspective.
In 2006, one initiative, the Netflix Prize, (2) created a focus on recommender systems and contributed to major advancements in the field during its three-year run.
The collaborative filtering approach is the most popular method of recommender systems [1], [10].
Recommender systems assist users by recommending items that can be interesting to users based on their previous buying behaviour (Zou, Wang, Wei, Li, & Yang, 2014).
For example, recommender nodes (R1, R2, R3) broadcasting their trust values about node j ("evaluated node"), as illustrated in Figure 1(b).
As a matter of fact, there could also be lots of new items in a real recommender system.
Therefore, a recommender system is an urgent demand for decrease in the time spent on design knowledge acquisition.
The evaluation and selection of recommender systems is a difficult decision making process.
Even if the album is not familiar to the reader, the recommender may be and vice versa.
0 is an activity-based recommender system for energy services.