Advances in Cross-Language Information Retrieval: Third by Carol Peters (auth.), Carol Peters, Martin Braschler, Julio

By Carol Peters (auth.), Carol Peters, Martin Braschler, Julio Gonzalo (eds.)

This ebook provides the completely refereed post-proceedings of a workshop via the Cross-Language evaluate discussion board crusade, CLEF 2002, held in Rome, Italy in September 2002.

The forty three revised complete papers provided including an creation and run info in an appendix have been rigorously reviewed and revised upon presentation on the workshop. The papers are equipped in topical sections on platforms review experiments, go language and extra, monolingual experiments, mostly domain-specific info retrieval, interactive concerns, cross-language spoken record retrieval, and cross-language assessment matters and initiatives.

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Additional info for Advances in Cross-Language Information Retrieval: Third Workshop of the Cross-Language Evaluation Forum, CLEF 2002 Rome, Italy, September 19–20, 2002 Revised Papers

Example text

Decompounding is helpful in monolingual retrieval, it is also helpful in bilingual retrieval to German from other languages such as English. Table 9 shows the performances of three bilingual retrieval to German with and without decompounding. 78%. An English phrase of two words may be translated into a German phrase of two words, or into a compound. For example, in topic 111, the English phrase computer animation became ComputerAnimation in the title field, but Computer Animation in the description field.

Then all the terms are ranked in decreasing order by their weight wt . The top-ranked k terms are added to the initial query to create a new query. Some of the selected terms may be among the initial query terms. 5. The rationale for assigning weights to the selected terms that are not among the initial query terms is that the selected terms are considered not as important as the initial query terms, so the weights assigned to them should fall in the range of 0 to 1, exclusive. 5, expecting that the query length will be doubled after query expansion.

The first approach translates the source topics into all the document languages in the document collection. Then monolingual retrieval is carried out separately for each document language, resulting in one ranked list of documents for each document language. Finally the intermediate ranked lists of retrieved documents, one for each language, are merged to yield a combined ranked list of documents regardless of language. The second approach translates a multilingual document collection into the topic language.

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