Dismiss
InnovationQ will be updated on Sunday, Oct. 22, from 10am ET - noon. You may experience brief service interruptions during that time.
Browse Prior Art Database

Mapping algorithm with rich relationship expression and higher-order abstraction

IP.com Disclosure Number: IPCOM000212126D
Original Publication Date: 2011-Oct-31
Included in the Prior Art Database: 2011-Oct-31
Document File: 4 page(s) / 601K

Publishing Venue

Microsoft

Related People

Jerre McQuinn: INVENTOR [+5]

Abstract

The invention empowers a non-technical business user to easily establish a central master of product relationship rules. It provides flexibility in the specification of relationship functionality and in the rules for membership in a collection. It implements a higher-order specification (“any” source relates to “same” target) and stores the data efficiently with automatic updates when data is created or retired. Key aspects to protect include: 1. Relationship types are richly specified. 2. Calculating members of collections a) Attribute-based rules for collection membership b) Dynamic joins for optimal performance c) Universal policy for all collections d) Storage efficiency) 3. “Any-Same” Higher-Order Abstraction

This text was extracted from a Microsoft Word document.
At least one non-text object (such as an image or picture) has been suppressed.
This is the abbreviated version, containing approximately 70% of the total text.

Document Author (alias)

Jerre McQuinn

Defensive Publication Title 

Mapping algorithm with rich relationship expression and higher-order abstraction

Name(s) of All Contributors

Jerre McQuinn

Gabor Melli

Shehzad Qureshi

George Ngo

Mike Lockhart

Summary of the Defensive Publication/Abstract

The invention empowers a non-technical business user to easily establish a central master of product relationship rules.  It provides flexibility in the specification of relationship functionality and in the rules for membership in a collection.  It implements a higher-order specification (“any” source relates to “same” target) and stores the data efficiently with automatic updates when data is created or retired.  Key aspects to protect include: 

1.     Relationship types are richly specified.

2.     Calculating members of collections

a)     Attribute-based rules for collection membership

b)    Dynamic joins for optimal performance

c)     Universal policy for all collections

d)    Storage efficiency)

3.     “Any-Same” Higher-Order Abstraction

 

Description: 

Business utility:  The diagram below depicts that many different relationship types ( renews, steps up, fulfills with) can be specified between any given collection, and in the lower left hand list of part numbers it illustrates that a collection can include (by rule specification) multiple part numbers.  Relationship types can be self-referential (Office Standard SA renews with Office Standard SA).

1. Rich Relationship Type Specification:  The diagram below shows how a user defines a relationship type with metadata that indicates the name, description, and whether the relationship type is forward (from left to right) or inverse (from right to left).  A relationship type can be specified to be bi-directional, typically used for specifying equivalencies.  The user specifies whether the collections are calculated and saved with many members or having only a single (individual to individual) member. Metadata about the relationship type is published in the result set.

2a. Rules-based Collection Membership: 

TO collecti...