This paper deals with translation ambiguity and target polysemy problems together. Two monolingual balanced corpora are employed to learn word co-occurrence for translation ambiguity resolution, and augmented translation restrictions for target polysemy resolution. Experiments show that the model achieves 62.92% of monolingual information retrieval, and is 40.80% addition to the select-all mode...

Eurospider participated in both the multilingual and monolingual retrieval tasks for CLEF 2001. Our multilingual experiments, the main focus of this year’s work, combine multiple approaches to cross-language retrieval: machine translation, similarity thesauri, and machine-readable dictionaries. We experimented with both query translation and document translation. The monolingual experiments foc...

This paper reports the methods and procedures we took in the CLIR track of NTCIR3. In monolingual subtasks we mainly describe index representation and word segmentation method. We use hybrid model integrating MT approach and dictionary-based approach in bilingual and multilingual subtasks. The method for combining the monolingual retrieval results to produce the final rank list is explained in ...

Thomson Legal and Regulatory participated in the monolingual, the bilingual and the multilingual tracks. Our monolingual runs added Swedish to the languages we had submitted in previous participations. Our bilingual and multilingual efforts used English as the query language. We experimented with dictionaries and similarity thesauri for the bilingual task, while we used machine translations in ...

The CLEF-2006 Cross-Language Speech Retrieval (CLSR) track included two tasks: to identify topically coherent segments of English interviews in a known-boundary condition, and to identify time stamps marking the beginning of topically relevant passages in Czech interviews in an unknown-boundary condition. Five teams participated in the English evaluation, performing both monolingual and cross-l...

Translated bi-texts contain complementary language cues, and previous work on Named Entity Recognition (NER) has demonstrated improvements in performance over monolingual taggers by promoting agreement of tagging decisions between the two languages. However, most previous approaches to bilingual tagging assume word alignments are given as fixed input, which can cause cascading errors. We observ...

Russian-English bilingual and English monolingual participants were tested on the Picture-Word Interference task modified for use with an eye-tracker. Distractor words were 1) non-words in English, but viable phonological words in Russian, 2) control bigram matched non-word stimuli, and 3) English translations of the Russian words. Russian-English bilinguals looked at the phonological Russian w...