  We discuss two techniques used to characterize bibliographic records based on
their similarity to and relationship with the contents of the NASA Astrophysics
Data System (ADS) databases. The first method has been used to classify input
text as being relevant to one or more subject areas based on an analysis of the
frequency distribution of its individual words. The second method has been used
to classify existing records as being relevant to one or more databases based
on the distribution of the papers citing them. Both techniques have proven to
be valuable tools in assigning new and existing bibliographic records to
different disciplines within the ADS databases.
