Introduction

High volume of information in Internet led to the development of novel techniques for managing of data, specially when we deal with information in multiple languages. There are sufficient example scenarios in which users may be interested in information which is in a language other than their own native language. A common language scenario is where a user has some comprehension ability for a given language but s/he is not sufficiently proficient to confidently specify a search request in that language. Thus, a search system that can deal with this problem should be of a high benefit. The World Wide Web (WWW) is a natural setting for cross-lingual information retrieval; the European Union is a typical example of a multilingual scenario, where multiple users have to deal with information published in at least 20 languages.

In order to reinforce research in this area, CLEF (Cross-Language Evaluation Forum) has been compiling a set of multi-lingual corpora and promoting the evaluation of multiple multi-lingual information retrieval systems for diverse kinds of data [5]. A particular task for the evaluation of such systems that deal with information on the web has been set up this year as a part of CLEF. This forum was named WebCLEF, and the best description of this particular task can be seen in [14]. In WebCLEF, three subtasks were defined within this year: mixed monolingual, multilingual, and bilingual English to Spanish.

This paper reports results on the evaluation of a Cross-Language Information Retrieval System (CLIRS) for the bilingual English to Spanish subtask of WebCLEF 2005. A document indexing reduction is proposed, in order to improve precision of CLIRS and to diminish the storing space on such systems. Our proposal is based on the use of the Transition Point (TP) technique, which is somehow a method that obtains important terms from a document. We evaluate different percentages of TP over a subset of EuroGOV corpus [13], and we observed that it is possible to improve precision results by reducing the number of terms for a given corpus.

The next section describes our information retrieval system in detail. Section 3 briefly introduces the corpus used in our experiments, and the results obtained after evaluation. Finally, a discussion of our experiments is presented.