The Dempster Shafer theory of evidence concerns the elicitation and manipulation
of degrees of belief rendered by multiple sources of evidence to a common
set of propositions. Information indexing and retrieval applications use a variety
of quantitative means - both probabilistic and quasi-probabilistic - to represent
and manipulate relevance numbers and index vectors. Recently, several
proposals were made to use the Dempster Shafes model as a relevance calculus
in such applications. The paper provides a critical review of these proposals,
pointing at several theoretical caveats and suggesting ways to resolve them.
The methodology is based on expounding a canonical indexing model whose
relevance measures and combination mechanisms are shown to be isomorphic
to Shafer's belief functions and to Dempster's rule, respectively. Hence, the
paper has two objectives: (i) to describe and resolve some caveats in the way
the Dempster Shafer theory is applied to information indexing and retrieval,
and (ii) to provide an intuitive interpretation of the Dempster Shafer theory, as
it unfolds in the simple context of a canonical indexing model.Information Systems Working Papers Serie
