Computer-based communication generation using phrases selected based on behaviors of communication recipients

Patent metadata

Field	Value
Publication number	US-RE50381-E
Application number	US-202217886426-A
Country	US
Kind code	E1
Filing date	Aug 11, 2022
Priority date	Nov 28, 2003
Publication date	Apr 15, 2025
Grant date	Apr 15, 2025

Abstract

A method and system for generating adaptive explanations for associated recommendations is disclosed. The adaptive explanations comprise a syntactical structure and associated phrases that are selected in accordance with usage behaviors and/or inferences associated with usage behaviors. The phrases included in an adaptive explanation may be selected through application of a non-deterministic process. The adaptive explanations may be beneficially applied to recommendations that are associated with content, products, and people, including recommendations that comprise advertisements.

First claim

What is claimed is:

1. A computer-based recommendation method comprising:
generating an affinity vector between a first user of a computer-based system and a plurality of computer-based objects based, at least in part, on the first user's behaviors; generating a similarity metric between the first user and a second user of the computer-based system based, at least in part, on the affinity vector of the first user and an affinity vector of the second user; generating a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric; and generating an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure.

2. The method of claim 1 wherein generating an affinity vector between a first user of a computer-based system and a plurality of computer-based objects based, at least in part, on the first user's behaviors comprises:
generating affinities between the user and a plurality of topic objects.

3. The method of claim 1 wherein generating a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric comprises:
recommending the second user to the first user.

4. The method of claim 1 wherein generating a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric comprises:
generating a recommendation responsive to the user's search request.

5. The method of claim 1 wherein generating a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric comprises:
generating a recommendation based on a recommendation preference setting established by the user.

6. The method of claim 1 wherein generating an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure comprises:
selecting phrases for inclusion in the explanation based on a frequency distribution.

7. The method of claim 1 wherein generating an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure comprises:
selecting phrases for inclusion in the explanation in accordance with the calculated confidence level of the recommendation.

8. A computer-based recommendation system comprising:
means to generate an affinity vector between a first user of a computer-based system and a plurality of computer-based objects based, at least in part, on the first user's behaviors; means to generate a similarity metric between the first user and a second user of the computer-based system based, at least in part, on the affinity vector of the first user and an affinity vector of the second user; means to generate a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric; and means to generate an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure.

9. The system of claim 8 wherein means to generate an affinity vector between a first user of a computer-based system and a plurality of computer-based objects based, at least in part, on the first user's behaviors comprises:
means to generate affinities between the user and a plurality of topic objects.

10. The system of claim 8 wherein means to generate a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric comprises:
means to recommend the second user to the first user.

11. The system of claim 8 wherein means to generate a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric comprises:
means to generate a recommendation responsive to the user's search request.

12. The system of claim 8 wherein means to generate a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric comprises:
means for generating a recommendation based on a recommendation preference setting established by the user.

13. The system of claim 8 wherein means to generate an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure comprises:
means to select phrases for inclusion in the explanation based on a frequency distribution.

14. The system of claim 8 wherein means to generate an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure comprises:
means to select phrases for inclusion in the explanation in accordance with the calculated confidence level of the recommendation.

15. A computer-based recommendation explanation system comprising:
means to generate a recommendation based, at least in part, on a plurality of usage behaviors; a syntactical structure for an explanation of an associated recommendation; a plurality of phrase arrays associated with the syntactical structure, wherein each phrase array comprises a plurality of phrases; a mapping of usage behaviors and corresponding phrase arrays appropriate to apply; and means to generate an explanation for the recommendation, wherein the explanation is generated in accordance with the syntactical structure and associated phrase arrays, and the mapping of usage behaviors with the corresponding phrase arrays appropriate to apply.

16. The system of claim 15 wherein means to generate an explanation for the recommendation, wherein the explanation is generated in accordance with the syntactical structure and associated phrase arrays, and the mapping of usage behaviors with the corresponding phrase arrays appropriate to apply comprises:
means to probabilistically select from alternative syntactical structures.

17. The system of claim 15 wherein means to generate an explanation for the recommendation, wherein the explanation is generated in accordance with the syntactical structure and associated phrase arrays, and the mapping of usage behaviors with the corresponding phrase arrays appropriate to apply comprises:
means to select phrases from a frequency distribution for inclusion in the explanation.

18. The system of claim 15 wherein means to generate an explanation for the recommendation, wherein the explanation is generated in accordance with the syntactical structure and associated phrase arrays, and the mapping of usage behaviors with the corresponding phrase arrays appropriate to apply comprises:
means to apply behavioral thresholds to trigger appropriate phrase arr

Assignees

• Gula Consulting Llc

Inventors

• Flinn Steven Dennis
• Moneypenny Naomi Felina

Classifications

• G06N3/004 Primary

  Artificial life, i.e. computing arrangements simulating life · CPC title

• G06N20/00

  Machine learning · CPC title

• G06Q30/0255

  based on user history · CPC title

• G06Q30/0631 Primary

  Recommending goods or services · CPC title