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A team of researchers from the Indian
Insititute of Technology Bombay, says it has developed a
search engine for the internet that is both
multi-lingual as well as meaning specific, giving it a
broader applicability and greater accuracy than existing
models. The engine uses Universal Networking Language
(UNL), the model and has integrated the user's language
requirement with the knowledge the user seeks
In a paper to be presented at the ongoing
International Conference on Universal Knowledge and
Language here, Dr Bhattacharya and his team of students,
Sarvjeet Singh, Tushar Chandra, Upmanyu Misra and Ushhan
D Gundevia argue that their search engine retrieves only
the knowledge that is relevant and attempts to bridge
the language gap by using an underlying, structured
language as a backhand translator.
Google, widely believed to be the best search engine,
is restricted only to English. According to an estimate
by the World Wide Web, English language content makes
for about 80 per cent of the trillion and trillion bytes
of textual information on the internet. Though other
language content is also catching up rapidly --
specially Chinese and South Asian languages -- the
digital divide between nations and people is still huge.
It is in the backdrop of this that the United Nations
began the UNL project in 1996. The universal networking
language is simply put, an electronic language. It uses
an EnConverter software to automatically convert natural
language text into UNL. Thirteen languages so far,
including Japanese, Chinese, Korean, Indonesian,
English, Hindi, Marathi, Arabic, Italian, Russian,
French, Spanish and Portuguese have deconverters in
place that automatically translates them to other
languages. With a lakh concepts in place, English boasts
of the largest wordnet, so far. |
