

Publisher: Edp Sciences
E-ISSN: 2261-236x|173|issue|03003-03003
ISSN: 2261-236x
Source: MATEC Web of conference, Vol.173, Iss.issue, 2018-06, pp. : 03003-03003
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
Abstract
This paper presents a Slope one improved algorithm based on user similarity and user interest forgetting function. Aiming at the problem of large number of users and a lot of noise data, the inactive users are filtered out by setting the threshold of user activity, and then the neighbors of the target users are obtained through the calculation of user similarity. According to interest forgetting function, and then filter out items that have less effect on current users to reduce the noise data to improve the accuracy of the algorithm. Experimental comparison shows that the improved algorithm has better accuracy than the commonly used weighted Slope one and two-pole Slope one.
Related content


Probabilistic Matrix Factorization Recommendation Algorithm with User Trust Similarity
MATEC Web of conference, Vol. 208, Iss. issue, 2018-09 ,pp. :


Community Mining Algorithm Based on Structural Similarity
MATEC Web of conference, Vol. 176, Iss. issue, 2018-07 ,pp. :


Research on stock similarity and community division based on user attention sequence
By Zhang Gaowei
MATEC Web of conference, Vol. 189, Iss. issue, 2018-08 ,pp. :


A Research on Network Similarity Search Algorithm for Biological Networks
MATEC Web of conference, Vol. 173, Iss. issue, 2018-06 ,pp. :