DECISION THEORETIC APPROACH TO TARGETED SOLICITATION BY MAXIMIZING EXPECTED PROFIT INCREASES

Patent №

US 8,103,537

Granted

2012-01-24

Filed 2005

Owner

MICROSOFT CORPORATION

AI components

3

ml · planning · evo

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

11257473

A decision theoretic approach to targeted solicitation, by maximizing expected profit increases, is disclosed. A decision theoretic model is used to identify a sub-population of a population to solicit, where the model is constructed to maximize an expected increase in profits. A decision tree in particular can be used as the model. The decision tree has paths from a root node to a number of leaf nodes. The decision tree has a split on a solicitation variable in every path from the root node to each leaf node. The solicitation variable has two values, a first value corresponding to a solicitation having been made, and a second value corresponding to a solicitation not having been made.

Machine learningPlanningEvolutionary computationG06Q 30/02G06Q 30/0201G06Q 30/0202G06Q 30/0203G06Q 30/0204G06Q 30/0207G06Q 30/0236G06Q 30/0247+2 more

AI classification

Machine learning0.84
Planning0.72
Evolutionary computation0.50
Natural language0.39
Knowledge representation0.39
AI hardware0.01
Vision0.01
Speech0.00

Ownership

MICROSOFT CORPORATION

assignment · 169490868

Assignors

CHICKERING, D. MAXWELL, HECKERMAN, DAVID E.

On an employer assignment, the assignors are typically the inventors.

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