Name
Abstract | ||
|---|---|---|
Cross-language information retrieval research has favored system-centered approaches in the past. The user is not an integral part of the translation and retrieval processes. In this paper, we investigate the problem of personalized cross-language information retrieval by exploiting query expansion techniques. The original query is augmented with terms mined from the useru0027s historical usage information in one language, with the aim of retrieving more relevant results in another language. Experiments semi-automatically constructed by using bilingual Wikipedia documents showed that in general personalized approaches work better than non-personalized approaches. We also found that an individual user model generated from one language can be used to enhance the personalized cross-language information retrieval. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/SMAP.2015.7370085 | SMAP |
Keywords | Field | DocType |
Personalized cross-language information retrieval, query expansion, user model, evaluation | Cognitive models of information retrieval,Query language,Human–computer information retrieval,Information retrieval,Query expansion,Computer science,Natural language processing,Artificial intelligence,Relevance (information retrieval),Document retrieval,Concept search,Cross-language information retrieval | Conference |
ISBN | Citations | PageRank |
978-1-5090-0242-9 | 2 | 0.37 |
References | Authors | |
9 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dong Zhou | 1 | 69 | 7.35 |
| Séamus Lawless | 2 | 111 | 30.18 |
| Jianxun Liu | 3 | 640 | 67.12 |
| Sanrong Zhang | 4 | 10 | 1.53 |
| Yu Xu | 5 | 2 | 0.37 |