Relevance feedback and cross-language information retrieval |
| |
| Authors: | Viviane Moreira Orengo Christian Huyck |
| |
| Institution: | School of Computing Science, Middlesex University, The Burroughs, London NW4 4BT, UK |
| |
| Abstract: | This paper presents a study of relevance feedback in a cross-language information retrieval environment. We have performed an experiment in which Portuguese speakers are asked to judge the relevance of English documents; documents hand-translated to Portuguese and documents automatically translated to Portuguese. The goals of the experiment were to answer two questions (i) how well can native Portuguese searchers recognise relevant documents written in English, compared to documents that are hand translated and automatically translated to Portuguese; and (ii) what is the impact of misjudged documents on the performance improvement that can be achieved by relevance feedback. Surprisingly, the results show that machine translation is as effective as hand translation in aiding users to assess relevance in the experiment. In addition, the impact of misjudged documents on the performance of RF is overall just moderate, and varies greatly for different query topics. |
| |
| Keywords: | Cross-language information retrieval Relevance feedback |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
