Name
Title | ||
|---|---|---|
Temporal Dynamic Recommendation Based On Data Imputation Through Association Analysis |
Abstract | ||
|---|---|---|
As a novel method for modelling user interest drift over time, we explore the session-based temporal dynamic recommendation, in which we impute missing rating in terms of users' association. Firstly, we mine user association groups through association analysis according to users' common preferences. Secondly, the user's consumption history is divided into sessions, and we impute vacant values based on the correlation and occupation of user association groups in each session. Thirdly, we model the user interest drift over time by latent Dirichlet allocation (LDA) in each session and predict user's current interest by an exponential decay function. Finally, we predict ratings on items for active user using neighbour-based collaborative filtering (CF). Experiments on a real dataset show that the proposed framework is more effective than previous methods on several tasks. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1504/IJCSE.2017.10006983 | INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING |
Keywords | Field | DocType |
recommender system, interest drift, data sparsity, data imputation, association analysis | Recommender system,Data mining,Latent Dirichlet allocation,Collaborative filtering,Computer science,Correlation,Artificial intelligence,Imputation (statistics),Machine learning | Journal |
Volume | Issue | ISSN |
15 | 1-2 | 1742-7185 |
Citations | PageRank | References |
0 | 0.34 | 17 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxiang Zhang | 1 | 167 | 15.28 |
| Xiayang Wang | 2 | 0 | 0.34 |
| Chunjing Xiao | 3 | 2 | 2.08 |
| yu sun | 4 | 32 | 13.07 |
| Yongwei Qiao | 5 | 0 | 0.68 |