Name
Title | ||
|---|---|---|
Personalized Parsimonious Language Models for User Modeling in Social Bookmaking Systems. |
Abstract | ||
|---|---|---|
This paper focuses on building accurate profiles of users, based on bookmarking systems. To achieve this goal, we define personalized parsimonious language models that employ three main resources: the tags, the documents tagged by the user and word embeddings that handle general knowledge. Experiments completed on Delicious data show that our proposal outperforms state-of-the-art approaches and non-personalized parsimonious models. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-56608-5_52 | ADVANCES IN INFORMATION RETRIEVAL, ECIR 2017 |
Keywords | Field | DocType |
User profile,Parsimonious models,Words embeddings | Data mining,World Wide Web,User profile,Information retrieval,Computer science,User modeling,General knowledge,Bookmarking,Language model | Conference |
Volume | ISSN | Citations |
10193 | 0302-9743 | 1 |
PageRank | References | Authors |
0.38 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nawal Ould Amer | 1 | 5 | 4.56 |
| Philippe Mulhem | 2 | 354 | 58.72 |
| Mathias Géry | 3 | 137 | 37.23 |