Author(s)
F. Neri
Abstract
The availability of a huge amount of textual data from a bewildering variety of
sources leads to the well-identified paradox based on which an overload of
information means no usable knowledge. In fact, up to 80% of electronic data is
textual. Moreover, the most valuable information is encoded in pages which are
written in various native languages, but are relevant even to non-native speakers.
The process of accessing all these raw data, heterogeneous for language used,
and transforming them into information is therefore inextricably linked to the
concepts of textual analysis and synthesis, hinging greatly on the ability to
master the problems of multilingualism. Through multilingual text mining, users
can get an overview of great volumes of textual data having a highly readable
grid, which helps them discover meaningful similarities among documents and
find all related information. This paper describes the approach used by
SYNTHEMA for multilingual text mining, showing the classification results on
around 600 breaking news items written in English, Italian and French.
1 Multilingual resources construction
Generally speaking, the manual construction and maintenance of multilingual
language resources is undoubtedly expensive, requiring remarkable efforts.
Being established in 1994 by computer scientists from the IBM Research Center,
with the expertise and skills suited to provide effective software solutions, as
well as carry out R&D in Natural Language Processing area, SYNTHEMA has
been involved in Machine Translation, Information Extraction and Text Mining
activities since 1996, primarily in the field of Technology Watch. The growing
availability of comparable and parallel corpora has pushed SYNTHEMA to
develop specific methods for semi-automatic updating of lexical resources. They
are based on Natural Language Understanding and Machine Learning. These
techniques detect multilingual lexicons from such corpora, by extracting all the
Keywords
Related Book
Other papers in this volume
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