Cross – Language Information Retrieval

Abstract

In today‘s growing nation, local database storage and retrieval is crucial for developing countries. A huge amount of information on Internet is available in numerous language that can be access by anybody at any time. Data Retrieval systems are fundamentally linguistic: the content or context of documents must be described, and the inquirers needed for documents must be expressed. These descriptions and expressions are most frequentlyarticulated in free or controlled vocabularies that have some of the same characteristics as natural language. Therefore, the processes of document description or request formulation must be strongly related to the processes of description and inquiry in natural language. Natural language processing is used to (a) preprocess the documents to extract content-carrying terms, (b) discover inter-term dependencies and build a conceptual hierarchy specific to the database domain, and (c) process the user's natural language requests into effective search queries. Since we assume that the information is primarily encoded as text, IR is also a natural language processing problem: to decide if a document is relevant to a given information need, one needs to be able to understand its content. CLIR deals with asking queries in one language and demand for retrieving documents in another language.This paper takes an overview of the new application areas of CLIR and reviews the approaches used in the process of CLIR research for query and document translation.