Name
Title | ||
|---|---|---|
A PLSA-based approach for building user profile and implementing personalized recommendation |
Abstract | ||
|---|---|---|
This paper proposes a method based on Probability Latent Semantic Analysis (PLSA) to analyze web pages that are of interest to the user and the user query co-occurrence relationship, and utilize the latent factors between the two co-occurrence data for building user profile. To make the weight of web pages that user isn't interested decay rapidly, a Fibonacci function is designed as the decay factor for representing the user's interests more exactly. The personalized recommendation is implemented according to the score of web pages. The experimental results showed that our approach was more effective than the other typical approaches to construct user profile. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72524-4_62 | APWeb/WAIM |
Keywords | Field | DocType |
personalized recommendation,web page,user profile,probability latent semantic analysis,decay factor,interested decay,co-occurrence data,user query co-occurrence relationship,plsa-based approach,latent factor,fibonacci function,web pages,latent semantic analysis | Static web page,Data mining,World Wide Web,User profile,Web page,Information retrieval,Computer science,User modeling,Probabilistic latent semantic analysis,Latent semantic analysis,Fibonacci number | Conference |
Volume | ISSN | Citations |
4505 | 0302-9743 | 4 |
PageRank | References | Authors |
0.53 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dongling Chen | 1 | 36 | 3.34 |
| Daling Wang | 2 | 207 | 41.35 |
| Ge YU | 3 | 1313 | 175.88 |
| Fang Yu | 4 | 4 | 0.53 |