  Name matching between multiple natural languages is an important step in
cross-enterprise integration applications and data mining. It is difficult to
decide whether or not two syntactic values (names) from two heterogeneous data
sources are alternative designation of the same semantic entity (person), this
process becomes more difficult with Arabic language due to several factors
including spelling and pronunciation variation, dialects and special vowel and
consonant distinction and other linguistic characteristics. This paper proposes
a new framework for name matching between the Arabic language and other
languages. The framework uses a dictionary based on a new proposed version of
the Soundex algorithm to encapsulate the recognition of special features of
Arabic names. The framework proposes a new proximity matching algorithm to suit
the high importance of order sensitivity in Arabic name matching. New
performance evaluation metrics are proposed as well. The framework is
implemented and verified empirically in several case studies demonstrating
substantial improvements compared to other well-known techniques found in
literature.
