OCCASION-BASED CONSUMER ANALYTICS

• US 20160260108A1
• Filed: 03/04/2016
• Published: 09/08/2016
• Est. Priority Date: 03/05/2015
• Status: Abandoned Application

• Current Assignee: Oculus360, Inc.
• Original Assignee: Oculus360, Inc.
• Inventors: Bracewell, David Brian
• Application Number:
  US15/061,701
• Publication Number:
  US 20160260108A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 40/20 Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A corpus of text data is accessed that includes a plurality of sentences and each of these sentences is parsed to determine, for each word, a corresponding meaning. A particular one of the sentences is determined to correspond to a particular occasion based on the determined meanings of one or more words of the particular sentence and is further determined to reference a product or service. A relationship is determined between the product or service and the particular occasion based on the particular sentence. One or more words of the particular sentence are determined to indicate a psychological characteristic of an author of the particular sentence. Consumer analytics data is generated to at least identify the relationship between the product or service and the particular occasion.

Claims

1. A method comprising:

identifying a corpus of text data comprising a plurality of sentences;

parsing, using a data processing apparatus, words of the plurality of sentences to determine, for each word, a corresponding meaning;

determining, using a data processing apparatus, that a particular one of the plurality of sentences corresponds to a particular occasion based on the determined meanings of one or more words of the particular sentence;

determining, using a data processing apparatus, that the particular sentence references a product or service based on the determined meanings of one or more words of the particular sentence;

determining, using a data processing apparatus, a relationship between the product or service and the particular occasion based on the particular sentence; and

determining, using a data processing apparatus, that one or more words of the particular sentence indicate a psychological characteristic of an author of the particular sentence; and

generating consumer analytics data to identify the relationship between the product or service and the particular occasion.

2. The method of claim 1, wherein the psychological characteristic comprises one of an attitudinal, sociocultural, personal, or behavior factor.

3. The method of claim 1, further comprising determining a type of the particular occasion from a plurality of occasion types based a determined meaning of one or more words of the particular sentence.

4. The method of claim 3, wherein the plurality of occasion types comprise celebratory, special, seasonal, weather-related, and temporal occasion types.

5. The method of claim 3, wherein determining the type of the particular occasion is based on a machine-learning model.

6. The method of claim 3, further comprising:

determining at least one other sentence in the plurality of sentences corresponds to another occasion of the same type as the particular occasion; and

defining an association between the particular sentence and particular sentence based on each sentence corresponding to the same occasion type.

7. The method of claim 1, further comprising:

determining, using a data processing apparatus, that one or more words of the particular sentence corresponds to a consumer expression of sentiment relating to the product or service; and

determining a relationship between the particular occasion and the consumer expression of sentiment relating to the product or service.

8. The method of claim 1, wherein determining that the particular sentence corresponds to a particular occasion is based on a machine-learning model.

9. The method of claim 1, further comprising annotating data describing the particular sentence to indicate a correspondence with the particular occasion.

10. The method of claim 1, further comprising determining whether the particular sentence includes a linguistic manifestation of consumer beliefs toward the product or service based on the determining meanings of words of the particular sentence.

11. The method of claim 1, further comprising determining whether the sentence includes a linguistic manifestation of social actions of a consumer based on the determining meanings of words of the particular sentence.

12. The method of claim 1, further comprising determining whether the sentence includes a linguistic manifestation of intentions of a consumer based on the determining meanings of words of the particular sentence.

13. The method of claim 1, further comprising determining, for each sentence, one or more words representing an aspect term based on the determining meanings of words of the particular sentence.

14. The method of claim 13, further comprising determining, for each aspect term, an aspect term polarity.

15. The method of claim 13, further comprising determining, for each aspect term, an aspect category.

16. The method of claim 13, further comprising determining, for each aspect category polarity, an aspect category polarity.

17. The method of claim 1, wherein the corpus comprises posts authored in a social network by a plurality of users.

18. The method of claim 1, wherein the corpus comprises reviews authored in association with an ecommerce website.

19. A machine-readable storage device comprising code operable, when executed by one or more processors, to:

identify a corpus of text data comprising a plurality of sentences;

parse words of the plurality of sentences to determine, for each word, a corresponding meaning;

determine that a particular one of the plurality of sentences corresponds to a particular occasion based on the determined meanings of one or more words of the particular sentence;

determine that the particular sentence references a product or service based on the determined meanings of one or more words of the particular sentence;

determine a relationship between the product or service and the particular occasion based on the particular sentence;

determine that one or more words of the particular sentence indicate a psychological characteristic of an author of the particular sentence; and

generate consumer analytics data to identify the relationship between the product or service and the particular occasion.

20. A system comprising:

one or more processor devices;

one or more memory elements;

a consumer analytics system, executable by the one or more processors to;

identify a corpus of text data comprising a plurality of sentences;

parse words of the plurality of sentences to determine, for each word, a corresponding meaning;

determine that a particular one of the plurality of sentences corresponds to a particular occasion based on the determined meanings of one or more words of the particular sentence;

determine that the particular sentence references a product or service based on the determined meanings of one or more words of the particular sentence;

determine a relationship between the product or service and the particular occasion based on the particular sentence;

determine that one or more words of the particular sentence indicate a psychological characteristic of an author of the particular sentence; and

generate consumer analytics data to identify the relationship between the product or service and the particular occasion.