recommender

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Recommender systems are utilized for personalizing information sources for users by guiding them in a personalized way to interesting items selected from myriad of available options (Lops et al.

Utilizing Learners' Negative Ratings in Semantic Content-based Recommender System for e-Learning Forum

The DealSmash Recommender System which is essentially the spam filter or modern marketer's funnel would help provide contextual awareness and personalized recommendations to retail customers.

MoIT to introduce system to help address spam SMS, emails issue

Tags and latent factor are used for android based food recommender system [9].

Diet-Right: A smart food recommendation system

In this paper linguistic variables [14] are represented using single valued neutrosophic numbers [13] for developing knowledge based recommender system.

A knowledge-based recommendation framework using SVN numbers

trust-aware recommender systems can help enable more items for recommendation while preserving competing predictive accuracy, where trust is propagated in trust networks to evaluate users' weights.

An effective method to incorporate trusted neighbors in recommender systems

The flash flood recommender tool available in the 2015 HMT-Hydro experiment was designed to contour areas [greater than or equal to] [0.

The HMT multi-radar multi-sensor hydro experiment

The first modern research paper on recommender systems (Resnick et al.

A short history of the RecSys Challenge

Two main categories of the recommender systems: content-based recommender systems and collaborative recommender systems.

Engineering mining a large scale data based on feature engineering, metadata, and ontologies

Recommender systems are decision support systems used in e-commerce to help navigate customers to the right product (Bauer & Nanopoulos, 2014; Cheung, Kwok, Law, & Tsui, 2003; Chung, Hsu, & Huang, 2013; Ekstrand, 2010; Gan & Jiang, 2013)

A novel latent factor model for recommender system

For example, node i ("evaluating node") requesting recommender nodes (R1, R2, R3) to share their trust values about node j ("evaluated node"), as illustrated in Figure 1(a).

Filtering dishonest trust recommendations in trust management systems in Mobile Ad Hoc Networks

Interested applicants should submit: a one-page letter of application with contact information; a narrative of threeto-five pages (double-spaced) that describes the scope of the project and the need for funding; a current CV; a one-page budget for the project; and one letter of reference from a scholar who is familiar with your work (the letter should be sent separately by your recommender to the committee chair).

Society for American Music establishes new fellowship in honor of Anne Dhu McLucas

In a real recommender system, users usually present their interest by five numeric scores [10].