Open AccessContent-Based Personalized Dating Recommendation System
Author(s) -
Yujiao Hu,
Xiaolin Gui,
Xinyue Hu,
Cong Zeng,
Youqi Wu
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1314/1/012104
Subject(s) - similarity (geometry) , computer science , euclidean distance , rationality , recommender system , information retrieval , order (exchange) , eigenvalues and eigenvectors , degree (music) , data mining , artificial intelligence , image (mathematics) , physics , finance , quantum mechanics , political science , acoustics , law , economics
In order to improve the accuracy of recommendation on dating websites, a personalized recommendation algorithm aiming at dating objects is put forward. The algorithm firstly extracts the user’s personal characteristic information and defines quantification criteria to quantify the characteristics. Then, the characteristics will be weighted according to the users’ different degree of emphasis on the eigenvalue and similarity between users will be calculated with Euclidean distance. Finally, possible candidates will be recommended according to similarity. The rationality of the algorithm is verified by some experiments.