Databases and Systems

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7.
the information-retrieval metric of Wilbur (16), which measures similarity of two
bibliographic citations based on textual content. ¹
Within a single axis, entities may be inter-related through recursive relationships
of the parent-child type. This complicates the query process because of the need
to "explode"a query object instance, retrieving all its children prior to scanning
the association data. E.g., in the example above, the pars compacta is part of the
substantia nigra, which is part of the mid-brain. To process a query that asked for
anatomical locations of various receptors in the mid-brain, one would first have
to retrieve all "child" anatomical sites within the mid-brain and then search the
association data against this set of child sites.
A general representation of N-ary Associations
The sub-schema we propose to handle the case of N-ary associations (where N, the
number of axes, varies) is shown in fig. 1. (In this figure, table names are
Bold/Underlined, while primary keys are in italics. Arrows point from a foreign key
to a primary key.) The Classes and Objects tables have been mentioned earlier in
connection with the Object Dictionary approach. The Facts table stores a unique
identifier, the Fact ID, and a textual narrative of the fact (for reasons described
shortly). There is a one-to-many link between the Facts table and a Citations table
(not shown in the figure).
¹
While some systems, such as NCBI's Entrez, store pre-computed sequence and
citation similarity scores for efficiency, such pre-computation must be done each time
new sequences or citations are added to the database. Such pre-computation is
justifiable only if the primarily purpose of the database is to assist similarity
searching (as in Entrez).