Cross Language Information Cross Language Information Exploitation of ArabicExploitation of Arabic

Dr. Elizabeth D. Liddy

Center for Natural Language ProcessingSchool of Information Studies

Syracuse University

Why Cross-Language Systems Matter

• There are approximately 4,500 living languages

• 32 million Americans switch from English to another language when they get home from work (U.S. Census 1990)

• Internationally, some who wish to do harm to the US communicate in other languages

• There are too few intel analysts who know the languages of interest

Internet Language Statistics

http://global-reach.biz/globstats/

Internet Language Statistics (2)

http://www.glreach.com/globstats/evol.html

How Cross-Language Retrieval Works

• User who speaks just one language asks their question of the system in that language

• Cross-language retrieval system: • Will have indexed documents (e.g. foreign reports,

emails, message traffic) written in other languages• Translates user query into language of the documents• Matches translated query against document index• Produces a ranked list of relevant documents that are

automatically translated into user’s language• User then reads documents in their own

language• User can now make more fully informed

decisions

SU’s Cross-Language Retrieval Research

• Have produced systems for French, Spanish, Japanese

– DARPA, Intel, & corporate funding of $3.5 million • Currently working in Dutch and Chinese

– 2nd demo is of cross-language English-Chinese on a patent database from China

• Today’s funding announcement will enable us to specialize our current cross-language retrieval capabilities for Arabic

• Future work on information extraction and visualization in Arabic is of keen interest

1. LIVIA – English/English IR System

• Accepts users’ natural language expressions of complex information needs

• Provides precise retrieval against government compiled documents about terrorist activities

• Core technology funded by DARPA and Syracuse Research Corporation

• Demo’d by Ozgur Yilmazel

2. English-Chinese Retrieval Demo

• Cross – Language Retrieval of English queries against a Chinese patent database– Development funded by Unilever Corp, a

multinational corporation which owns 140 companies in more than 100 countries

• Jiang Ping Chen– PhD student in School of Information Studies

Look to the Future

• Incorporate the next level of sophistication in Information Exploitation into Arabic

• Here seen in English– Adds Information Extraction as next step to

Information Retrieval

• Seek your ongoing support for its extension into Arabic

Thank You!

Questions?

Care to try a query on LIVIA!