Computerized method and apparatus for automatically generating a natural language description of a person's activities

• US 20060259293A1
• Filed: 05/11/2005
• Published: 11/16/2006
• Est. Priority Date: 05/11/2005
• Status: Abandoned Application

• Current Assignee: Orange S.A.
• Original Assignee: Orange S.A.
• Inventors: Orwant, Jonathan Lee
• Application Number:
  US11/127,976
• Publication Number:
  US 20060259293A1
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 40/143 Markup, e.g. Standard Generalized Markup Language [SGML] or Document Type Definition [DTD]
• CPC Class Codes: G06F 40/56 Natural language generation

Abstract

A computerized method to gather, store and process data related to activities in which the person had been engaged, and to generate a natural language description summarizing the person'"'"'s activities. The description can then be transmitted to a remote computer for use by various computer applications, such as a blog.

Claims

1. A computerized method for automatically composing a natural language summary of a person'"'"'s activities, comprising:

obtaining data related to activities in which the person has engaged;

distinguishing more meaningful data from less meaningful data contained in the obtained data; and

composing a natural language summary of the person'"'"'s activities from said more meaningful data.

2. The method of claim 1, wherein the step of obtaining data comprises making measurements automatically with activity sensors to output a machine-readable signal.

3. The method of claim 2, wherein the step of obtaining data comprises automatically making the measurements with said activity sensors at preset periodic time intervals.

4. The method of claim 3, wherein the step of obtaining data comprises organizing the obtained data as a function of time.

5. The method of claim 4, wherein the step of gathering data comprises organizing the obtained data as a function of activities.

6. The method of claim 2, wherein the step of distinguishing more meaningful data from less meaningful data comprises:

organizing said obtained data into sets of sensor observations; and

determining a relative importance value for each of said sets of sensor observations.

7. The method of claim 6, further comprising the step of obtaining a value related to the amount of a person'"'"'s attention required by a particular activity;

and

wherein the step of determining a relative importance value applies the obtained attention value obtained for the particular activity.

8. The method of claim 6, wherein the composing step comprises composing a natural language summary for only sets of sensor observations having a relative importance value that exceeds a preset threshold.

9. The method of claim 1, further comprising the step of transmitting the natural language summaries for publication.

10. A method, based on using data obtained about activities engaged in by a person, for distinguishing more meaningful data from less meaningful data contained in the obtained data, comprising the steps of:

for each activity, determining a first weight based on the history of the person;

for each activity, determining a second weight based on the history of a population; and

for each activity, combining the first and second weights to derive an importance value.

11. The method of claim 10, wherein the first weight for a particular activity is determined based on occurrences of such activity in the history of the person.

12. The method of claim 10, wherein the first weight for a particular activity is determined based on durations for such activity in the history of the person.

13. The method of claim 10, wherein the second weight for a particular activity is determined based on occurrences of such activity in the history of the population.

14. The method of claim 10, wherein the second weight for a particular activity is determined based on durations for such activity in the history of the population.

15. The method of claim 10, further comprising the steps of:

obtaining a value related to the amount of a person'"'"'s attention required by a particular activity; and

wherein said step of deriving an importance value comprises combining the obtained attention value obtained for the particular activity with the first and second weights determined for the particular activity.

16. A method, based on using data obtained about at least one activity engaged in by a person, for automatically composing a natural language summary of such at least one activity, comprising the steps of:

creating a paragraph structure related to the at least one activity;

creating a sentence structure to respectively summarize at least a component of the at least one activity, wherein the natural language used in the sentences is based on the obtained data;

selecting verbs for insertion into said sentence structure; and

selecting conjunctions for joining the paragraphs and/or sentences to form the summary.

17. The method of claim 16, wherein the paragraphs are chosen via a queue ordered by relative importance of an activity in comparison with the person'"'"'s other activities.

18. The method of claim 16, wherein the paragraphs are chosen via a queue randomly ordered with likelihoods related to relative importance of an activity in comparison with the person'"'"'s other activities.

21. The method of claim 16, wherein the sentences are chosen via a queue randomly ordered with likelihoods related to relative importance of an activity in comparison with the person'"'"'s other activities.

22. The method of claim 16, wherein the verbs are chosen via a randomized circular buffer.

23. The method of claim 16, wherein the phrases are chosen via a randomized circular buffer.

24. The method of claim 16, wherein the conjunctions are chosen via a randomized circular buffer.

25. The method of claim 16, further comprising the step of selecting for the paragraphs and/or sentences introductory phrases corresponding to an aspect of activity usage related to unusualness.