METHODS AND APPARATUS TO FACILITATE DYNAMIC CLASSIFICATION FOR MARKET RESEARCH
Methods and apparatus to facilitate dynamic classification for market research are disclosed. Example disclosed methods include constructing, using a programmed processor based on data for a sample population and a first set of input variables, a self-organizing map classifying the sample population according to a plurality of classes defined in the map using fuzzy class membership. Example disclosed methods include extracting the fuzzy class membership for the sample population from the map. Example disclosed methods include correlating fuzzy class membership with behavior data for the sample population to determine a likely class behavior for the plurality of classes. Example disclosed methods include using fuzzy class membership and the likely class behavior to provide a predictive market output in response to a query.
1 .- 31 . (canceled)
32 . A tangible computer readable storage medium having instruction that, when executed, cause a machine to:
construct, based on data for a sample population and a first set of input variables, a self-organizing map classifying the sample population according to a plurality of classes defined in the map using fuzzy class membership;
extract the fuzzy class membership for the sample population from the map;
correlate fuzzy class membership with behavior data for each class in the sample population to determine a likely class behavior for the plurality of classes; and
use fuzzy class membership and the likely class behavior to provide a predictive market output in response to a query.
33 . The computer readable storage medium of claim 32 , wherein the fuzzy class membership classifies each member of the sample population to be a member in each of the plurality of classes.
34 . The computer readable storage medium of claim 33 , wherein the map classifies each member of the sample population with a primary class and a lesser percentage membership in each of the remaining plurality of classes.
35 . The computer readable storage medium of claim 32 , having instructions that, when executed, cause the machine to, identify similar classes based on an analysis of class characteristics from the map.
36 . The computer readable storage medium of claim 32 , having instructions that, when executed, cause the machine to construct a plurality of self-organizing maps based on a plurality of input vectors.
37 . The computer readable storage medium of claim 32 , having instructions that, when executed, cause the machine to determine fuzzy class membership and behavior for a universe of people based on the fuzzy class membership and fuzzy class behavior.
38 . The computer readable storage medium of claim 37 , wherein the universe of people includes at least one of a population of a state, a population of a region, or a population of a country.
39 . The computer readable storage medium of claim 32 , having instructions that, when executed, cause the machine to re-construct, based on data for a sample population and a second set of input variables, the self-organizing map classifying the sample population according to the plurality of classes defined in the map using fuzzy class membership.
40 . An apparatus comprising:
a market behavior data processor particularly programmed to:
construct, based on data for a sample population and a first set of input variables, a self-organizing map classifying the sample population according to a plurality of classes defined in the map using fuzzy class membership;
extract the fuzzy class membership for the sample population from the map;
correlate fuzzy class membership with behavior data for each class in the sample population to determine a likely class behavior for the plurality of classes; and
use fuzzy class membership and the likely class behavior to provide a predictive market output in response to a query.
41 . The apparatus of claim 40 , wherein the fuzzy class membership classifies each member of the sample population to be a member in each of the plurality of classes.
42 . The apparatus of claim 41 , wherein the map classifies each member of the sample population with a primary class and a lesser percentage membership in each of the remaining plurality of classes.
43 . The apparatus of claim 40 , wherein the processor is to:
identify similar classes based on an analysis of class characteristics from the map.
44 . The apparatus of claim 40 , wherein the processor is to:
construct a plurality of self-organizing maps based on a plurality of input vectors.
45 . The apparatus of claim 40 , wherein the processor is to:
determine fuzzy class membership and behavior for a universe of people based on the fuzzy class membership and fuzzy class behavior.
46 . The apparatus of claim 40 , wherein the processor is to:
re-construct, based on data for a sample population and a second set of input variables, the self-organizing map classifying the sample population according to the plurality of classes defined in the map using fuzzy class membership.
47 . (canceled)
48 . A method comprising:
constructing a self-organizing map classifying respondents according to a first set of input variables defining parameters associated with the respondents, the self-organizing map clustering and distributing the respondents according to a plurality of classes defined in the self-organizing map using fuzzy class membership; and
predicting, based on the fuzzy class membership and respondent behavior data, a class behavior.
49 . The method of claim 48 , wherein the self-organizing map includes a plurality of layers, each layer corresponding to an input variable in the set of input variables.
50 . The method of claim 48 , wherein predicting a class behavior is triggered by a request for a market behavior prediction.
51 . The method of claim 48 , further including extrapolating universe fuzzy class membership based on the respondent fuzzy class membership.
52 . The method of claim 48 , further including constructing a second self-organizing map classifying respondents according to a second set of input variables defining parameters associated with the respondents.