Method and system to predict a data value
First Claim
1. A computer based system for predicting a data value, said system comprising:
- a processor capable of executing machine instructions;
the machine instructions including a means for predicting a predicted data value of a first data set at a predicted dimension value utilizing a focus topic profile and a means for analyzing a second data set using a latent variable method;
the latent variable method using at least one focus feature from a third data set to create at least one focus topic from the second data set; and
the focus topic profile comprises at least one focus topic value of the at least one focus topic from the second data set.
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Abstract
Embodiments of the present invention include methods and systems for predicting the likelihood of topics appearing in a set of data such as text. A number of latent variable methods are used to convert the data into a set of topics, topic values and topic profiles. A number of time-course methods are used to model how topic values change given previous topic profiles, or to find historical times with similar topic values and then projecting the topic profile forward from that historical time to predict the likelihood of the topics appearing. Embodiments include utilizing focus topics, such as valence topics, and data representing financial measures to predict the likelihood of topics. Methods and systems for modeling data and predicting the likelihood of topics over other dimensions are also contemplated.
46 Citations
31 Claims
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1. A computer based system for predicting a data value, said system comprising:
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a processor capable of executing machine instructions; the machine instructions including a means for predicting a predicted data value of a first data set at a predicted dimension value utilizing a focus topic profile and a means for analyzing a second data set using a latent variable method; the latent variable method using at least one focus feature from a third data set to create at least one focus topic from the second data set; and the focus topic profile comprises at least one focus topic value of the at least one focus topic from the second data set. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A computer based system for predicting a data value, said system comprising:
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a processor capable of executing machine instructions; the machine instructions including a means for predicting a predicted data value of a first data set at a predicted dimension value utilizing a focus topic profile; and
the means for predicting the predicted data value further comprises a modeling package capable of;receiving a base dimension value having a base focus topic value; receiving a predicted dimension value having a difference dimension value from the base dimension value; analyzing the focus topic profile over at least one dimension value to identify a most similar focus topic value to the base focus topic value; the dimension value at the most similar focus topic value being a selected dimension value; and selecting at least one data value from the first data set at the difference dimension value from the selected dimension value as the predicted data value at the predicted dimension value. - View Dependent Claims (8, 9, 10, 11)
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12. A computer based system for predicting a data value, said system comprising:
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a processor capable of executing machine instructions on a first set of data comprising financial data; and the machine instructions including a means for transforming a second set of data over at least one dimension value to create a topic profile and a means for predicting a predicted data value of the first set of data at a predicted dimension value; and the means for predicting the predicted data value of the first set of data further comprises a modeling package capable of; receiving a base dimension value having a base topic value; receiving the predicted dimension value having a different dimension value from the base dimension value; analyzing the topic profile over the at least one dimension value to identify a most similar topic value to the base topic value; the dimension value at the most similar topic value being a selected dimension value; and selecting at least one data value from the first data set at the difference dimension value from the selected dimension value as the predicted data value at the predicted dimension value. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20)
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21. A method for predicting a data value, said method comprising:
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receiving a first data set; predicting a predicted data value of the first data set at a predicted dimension value utilizing a focus topic profile; analyzing a second set of data using a latent variable method; the latent variable method using at least one focus feature from a third data set to create at least one focus topic from the second data set; and the focus topic profile comprises at least one focus topic value of the at least one focus topic from the second set of data. - View Dependent Claims (22, 23, 24, 25, 26)
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27. A method for predicting a data value, said method comprising;
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receiving a first data set; receiving a base dimension value having a base focus topic value; receiving a predicted dimension value having a difference dimension value from the base dimension value; analyzing a focus topic profile over at least one dimension value to identify a most similar focus topic value to the base focus topic value; the dimension value at the most similar focus topic value being a selected dimension value; and selecting at least one data value from the first data set at the difference dimension value from the selected dimension value as the predicted data value at the predicted dimension value. - View Dependent Claims (28, 29, 30, 31)
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Specification