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Document translation retrieval based on statistical machine translation techniques (2011)
| Content Provider | CiteSeerX |
|---|---|
| Author | Sánchez-Martínez, Felipe Carrasco, Rafael C. |
| Abstract | We compare different strategies to apply statistical machine translation techniques in order to retrieve documents which are a plausible translation of a given source document. Finding the translated version of a document is a relevant task, for example, when building a corpus of parallel texts that can help to create and to evaluate new machine translation systems. In contrast to the traditional settings in cross-language information retrieval tasks, in this case both the source and the target text are long and, thus, the procedure used to select what words or phrases will be included in the query has a key effect on the retrieval performance. In the statistical approach explored here, both the probability of the translation and the relevance of the terms are taken into account in order to build an effective query. 1 |
| File Format | |
| Journal | Applied Artificial Intelligence |
| Language | English |
| Publisher Date | 2011-01-01 |
| Access Restriction | Open |
| Subject Keyword | Statistical Machine Translation Technique Document Translation Retrieval Different Strategy Source Document Plausible Translation Target Text Retrieval Performance Key Effect Statistical Approach Translated Version Cross-language Information Retrieval Task Effective Query Relevant Task New Machine Translation System Traditional Setting Parallel Text |
| Content Type | Text |
| Resource Type | Article |
