Quantum Teleportation with an Accelerated Partner in Open System

Xiang, Maohuai; Jing, Jiliang

doi:10.4236/jqis.2012.24016

Cited by 2 publications

(1 citation statement)

References 33 publications

(34 reference statements)

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“…We use MAE (Mean Absolute Error) and precision to evaluate the results. Assuming that P is the prediction rating set, T is the actual rating set, R(u) is the predicted movies, T(u) is the movies that user really likes, then these three measures can be defined as follows: (11) In (10), we supposed the rating scores that equal or greater than 3 are recommended. We used different number of neighbors and recommended movies for testing.…”

Section: Resultsmentioning

confidence: 99%

Collaborative Filtering Recommendation Algorithm Applying Multi-Criteria Decision Making

Jiang

Zhu

Wang

2014

AMR

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In order to solve the problem of ignoring items’ attributes in single criteria collaborative filtering recommendation algorithm, a collaborative filtering recommendation algorithm based on multi-criteria decision making was proposed. Multi-criteria decision making was used during the computing of users’ similarity in the algorithm. By averaging all the similarities of sub evaluation with their weight, the algorithm chose the nearest neighbors. Finally, the algorithm used several nearest neighbors to get the recommendation results. Experiments show that the algorithm can find the nearest neighbors more similar after detailing evaluation, and make better predictions for the target users.

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Section: Resultsmentioning

confidence: 99%