Research and Application of Personalized Modeling Based on Individual Interest in Mining
Baocheng Huang and
Guang Yu
Abstract and Applied Analysis, 2014, vol. 2014, issue 1
Abstract:
Weibo services, provided by the service providers, is simple and changeless. The research based on the content of microblog reflects the user’s personalized features. The method has important significance to improve user satisfaction and expand the scale of users. First, the interest classification problem called multiclass classification algorithm is proposed based on improving support vector machine of binary tree. Second, an improved model of mixed interest based on implicit feedback is proposed. This method is based on the shortcomings of the establishment of the interest model and the drift strategy in update phase among existing users. The improved model is applied to the user modeling of personalization, improving the authenticity and accuracy of the personalized modeling.
Date: 2014
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1155/2014/514295
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:514295
Access Statistics for this article
More articles in Abstract and Applied Analysis from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().