Name
Title | ||
|---|---|---|
Recommendation Algorithm Based on Graph-Model Considering User Background Information |
Abstract | ||
|---|---|---|
With the development of information technologies and increase scale of digital resources, personalized recommendation systems have come into the big picture of web2.0 technology. This paper proposed a graph-based recommendation algorithm using the user-resource rating data to construct a graph model and improves the model by adding user background information. The Random Walk with Restarts algorithm is applied to generate the final recommendation set. The improvement in accuracy on sparse data is illustrated by the experiments on the Movie Lens data set, comparing with the collaborative filtering algorithm. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/C5.2011.11 | C++ |
Keywords | Field | DocType |
sparse data,final recommendation set,collaborative filtering,digital resources,user background information,user-resource rating data,random walk,information technology,restarts algorithm,recommendation algorithm,movie lens data,recommender systems,graph model,web2.0 technology,random walk with restarts,internet,information resources,personalized recommendation,personalized recommendation system,graph-based recommendation algorithm,movielens dataset,graph theory,personal computing,graph-model,information technologies,personalized recommendation systems | Graph theory,Recommender system,Data mining,Collaborative filtering,Information technology,Computer science,Random walk,Algorithm,Sparse matrix,Information filtering system,The Internet | Conference |
ISBN | Citations | PageRank |
978-1-61284-390-2 | 2 | 0.36 |
References | Authors | |
22 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ziqi Wang | 1 | 47 | 4.63 |
| Ming Zhang | 2 | 1963 | 107.42 |
| Yuwei Tan | 3 | 32 | 2.36 |
| Wenqing Wang | 4 | 2 | 1.37 |
| Yuexiang Zhang | 5 | 2 | 0.36 |
| Ling Chen | 6 | 108 | 11.93 |