Name
Title | ||
|---|---|---|
A study of user profile representation for personalized cross-language information retrieval. |
Abstract | ||
|---|---|---|
Purpose - With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion. Design/methodology/approach - The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods. Findings - Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level. Originality/value - Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1108/AJIM-06-2015-0091 | ASLIB JOURNAL OF INFORMATION MANAGEMENT |
Keywords | Field | DocType |
Query expansion,Personalization,Automatic evaluation,Cross-language information retrieval,Topic models,User profile representation | User profile,Information retrieval,Query expansion,Computer science,Topic model,Cross-language information retrieval,Personalization | Journal |
Volume | Issue | ISSN |
68.0 | 4.0 | 2050-3806 |
Citations | PageRank | References |
2 | 0.39 | 29 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dong Zhou | 1 | 69 | 7.35 |
| Séamus Lawless | 2 | 111 | 30.18 |
| Xuan Wu | 3 | 11 | 2.21 |
| Wenyu Zhao | 4 | 11 | 2.21 |
| Jianxun Liu | 5 | 640 | 67.12 |