The Effect of Pseudo Relevance Feedback on MT-Based CLIR
نویسندگان
چکیده
In this paper, we identify factors that affect machine translation (MT) of a source query for cross-language information retrieval (CLIR) and empirically evaluate the effect of pseudo relevance feedback on crosslanguage retrieval performance. Our experiments demonstrate that, by using pseudo relevance feedback, we can significantly improve cross-language retrieval performance and achieve the level of monolingual retrieval.
منابع مشابه
Notes on Experiments with Pseudo Relevance Feedback and Data Merging In Cross-Language Retrieval
In the TREC-8 cross-language information retrieval (CLIR) track, we adopted the approach of using machine translation to prepare a source-language query for use in a target-language retrieval task. We empirically evaluated (1) the effect of pseudo relevance feedback on retrieval performance with two feedback vector length control methods in CLIR, and (2) the effect of multilingual data merging ...
متن کاملISCAS in CLIR at NTCIR-6: Experiments with MT and PRF
We participated in the English-Chinese cross-language information retrieval (CLIR) E-C tasks in NTCIR6. Considering the special feature of crossing two different languages in CLIR, our main concerns in our experiment are 1) to evaluate the appropriateness of MT as a means of query translation in CLIR, 2) to evaluate the effect of feedback in retrieval model to the performance of CLIR which has ...
متن کاملCLARIT TREC-8 CLIR Experiments
In the TREC-8 cross-language information retrieval (CLIR) track, we adopted the approach of using machine translation to prepare a source-language query for use in a target-language retrieval task. We empirically evaluated (1) the effect of pseudo relevance feedback on retrieval performance with two feedback vector length control methods in CLIR and (2) the effect of multilingual data merging e...
متن کاملToshiba BRIDJE at NTCIR-4 CLIR: Monolingual/Bilingual IR and Flexible Feedback
Toshiba participated in the Monolingual/Bilingual tasks at NTCIR-4 CLIR using our CLIR system called BRIDJE. We submitted 24 runs covering three topic languages (Japanese, English and Chinese) and two document languages (Japanese and English) and achieved the highest performances in the E-J-D, CJ-D, C-J-T, E-E-D, J-E-D, J-E-T subtasks. We had 12 more runs which we were not allowed to submit due...
متن کاملHighly Relevant Documents Lost in CLIR: Experiments with Dictionary Translation and Pseudo-Relevance Feedback
Research on cross-language information retrieval (CLIR) has typically been restricted to settings using binary relevance assessments. In this paper, we present evaluation results for dictionary-based CLIR using graded relevance assessments in a best match retrieval environment. A text database containing newspaper articles and a related set of 35 search topics were used in the tests. First, mon...
متن کامل