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Browse Prior Art Database

Weighted Wildcard Matching

IP.com Disclosure Number: IPCOM000118538D
Original Publication Date: 1997-Mar-01
Included in the Prior Art Database: 2005-Apr-01
Document File: 2 page(s) / 37K

Publishing Venue

IBM

Related People

Relson, PJ: AUTHOR

Abstract

Disclosed is a process that compares a multi-part input specification (in this case, a product definition which consists of owner, name, et al.) with a group of entries, each of which has the same parts, may have wildcard specifications, and determines the "best" match according to the following rules: o An exact match is better than a wildcard match. o The implementation processes the parameters in order such that an exact match on a parameter earlier in the list (e.g., OWNER) is better than an exact match on a parameter later in the list (e.g., NAME).

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Weighted Wildcard Matching

      Disclosed is a process that compares a multi-part input
specification (in this case, a product definition which consists of
owner, name, et al.) with a group of entries, each of which has the
same parts, may have wildcard specifications, and determines the
"best" match according to the following rules:
  o  An exact match is better than a wildcard match.
  o  The implementation processes the parameters in order such
      that an exact match on a parameter earlier in the list
      (e.g., OWNER) is better than an exact match on a parameter
      later in the list (e.g., NAME).

      The implementation performs a matching process on each part of
the multi-part input, in order, assigning a weight to each matching
process.  The weight for each part exceeds the sum of the weights for
all "later" parts.  A possible implementation of this is to assign
the weights as powers of two (e.g., the first weight is 2**30, the
next is  2**29, etc.).

      If the matching process finds an exact match, the "total
weight" is increased by the weight for that matching process.  If the
matching process finds a wildcard match, the total weight is not
increased.

      The implementation performs the multi-part matching process on
each eligible entry; the implementation considers the entry with the
highest resulting total weight that matched on all parts to be the
"best" match.

      Note that this process does not diff...