In the era of globalization, internet being accessible
and affordable has gained huge popularity and is widely being
used almost everywhere by Government, private organizations,
companies, banks, etc. as well as by individuals. It has empowered
its users to contribute to the creation of information on web
enabling them to use their native languages which consequently
has drastically increased the volume of web-accessible documents
available in languages other than English. This exponential
growth of information on the internet has also induced several
challenges before the information retrieval systems. Most of the
present monolingual information retrieval systems can retrieve
documents in the language of query only, missing the information
in other languages that may be more relevant to the user. The
need of information retrieval systems to become multilingual has
given rise to the research in Cross Language Information
Retrieval (CLIR) which can cross the language barriers and
retrieve more relevant results from documents in different
languages. This article is a review of motivation, issues, work and
challenges related to various CLIR approaches. Starting with the
most fundamental approaches of translation, it is attempted to
study and present a review of more advanced approaches for
enhancing the retrieval results in CLIR proposed by various
researchers working in this domain.
Comparing Weighting Models for Monolingual Information Retrieval