Name
Title | ||
|---|---|---|
Leveraging User Personality and Tag Information for One Class Collaborative Filtering. |
Abstract | ||
|---|---|---|
Recommender systems have been great tools for electronic market companies to satisfy customer. A large volume of information is generated by online users and how to appropriately provide personalized content is becoming more challenging. Traditional recommendation models are overly dependent on preference ratings and often suffer from the problem of "data sparsity". The one class collaborative filtering (OCCF) method is more applicable in the electronic market scenario yet it is insufficient for item recommendation. In this study, we develop a novel personality-tag-aware item recommendation framework, referred to as PT OCCF, in order to tackle the above challenges. We leverage user personality and tag information and OCCF models to improve recommendation performance. We conduct comprehensive experiments on a public dataset to verify the effectiveness of the proposed framework and methods. The results show that the proposed methods are effective in improving the performance of the baseline OCCF methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-00776-8_76 | ADVANCES IN MULTIMEDIA INFORMATION PROCESSING, PT I |
Keywords | Field | DocType |
Electronic market,Recommender system,Personality,Tag,OCCF | Recommender system,Collaborative filtering,Leverage (finance),Information retrieval,Pattern recognition,Computer science,Artificial intelligence,Personality | Conference |
Volume | ISSN | Citations |
11164 | 0302-9743 | 1 |
PageRank | References | Authors |
0.34 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianshan Sun | 1 | 192 | 17.65 |
| Deyuan Ren | 2 | 1 | 0.34 |
| Dong Xu | 3 | 7616 | 291.96 |