Combining partially independent belief functions
  The theory of belief functions manages uncertainty and also proposes a set of
combination rules to aggregate opinions of several sources. Some combination
rules mix evidential information where sources are independent; other rules are
suited to combine evidential information held by dependent sources. In this
paper we have two main contributions: First we suggest a method to quantify
sources' degree of independence that may guide the choice of the more
appropriate set of combination rules. Second, we propose a new combination rule
that takes consideration of sources' degree of independence. The proposed
method is illustrated on generated mass functions.
