JHU Experiments in Monolingual Farsi Document Retrieval at CLEF 2009

A first choice for adapting the previous word-level alignment algorithm to the case of n-grams could be just to adapt the contingency table to the new context, by considering that

In our first participation in the Cross Language Evaluation Forum we focused on the development of a  retrieval  system  which  provides  a  good  baseline 

Table 14 shows the retrieval effectiveness for various query translation combinations (concatenation of the translations produced by two or more MT systems) when using the

However, 54% of the words in the list are nouns, and since Light2 removes all noun cases just like the Heavy stemmer, but unlike Light1 and Medium, these scores make sense.. The

The fused lists shown in Table 10 are as follows: 1: monolingual results merged, 2: English and translated French documents merged into a single collection, combined retrieval run

[2] A.M.Lam-Adesina and G.J.F.Jones, EXETER AT CLEF 2003: Experiments with Machine Translation for Monolingual, Bilingual and Multilingual Retrieval, In Proceedings of the CLEF

ITC-irst submitted 4 monolingual runs in French, German, Italian, and Spanish, 4 Italian-Spanish bilin- gual runs, 2 German-Italian bilingual runs, and 4 small multilingual runs

Query expansion from the merged document collection (used for the multilingual task) of Spanish, English, French, and German also resulted in improvement in retrieval performance,