Support for Interactive Document Selection in Cross-Language Information Retrieval

Abstract As digital libraries grow to global scale, the provision of interactive access to content in many languages will become increasingly important. In systems that support query-based searching, the presence of multilingual content will affect both the search technology itself and the user interface components that support query formulation, document selection and query refinement. This article describes the interactions among these components and presents a practical way of evaluating the adequacy of the selection interface. A categorization-based model for the user's selection process is presented and an experimental methodology suitable for obtaining process centered results in this context is developed. The methodology is applied to assess the adequacy of a selection interface in which multiple candidate translations for a term can be simultaneously presented. The results indicate that the modeled selection process is somewhat less effective when users are presented with multi-translation glosses from Japanese to English rather than materials generated originally in English, but that users with access to the gloss translations substantially outperform a Naive Bayes classification algorithm.