System and method for using data incident based modeling and prediction

Abstract

A system and method for enabling information extraction from large data sets (so-called “big data”) according to a new paradigm is disclosed. This system does not generate functions describing why certain inputs result in certain outputs. Instead, it creates incident mappings of inputs to outputs without regard to why inputs result in outputs. These mappings can be distributions or other data sets representative of different outcomes occurring. This enables several useful operations. For example, by providing a data set indicative of outputs that have historically occurred following a particular input, the disclosed system can be used to predict future outcomes with probabilities. For example, if a particular stock price pattern is provided as an input, the system generates an output data set indicating the probabilities of certain price behaviors following that input pattern. This data set can thus be used to predict future behavior. Other useful operations are disclosed herein.

The invention is claimed as follows: 
     
         1 . A system for providing an intelligent database comprising:
 a database; and   a server computer system, including one or more processors, in communication with the database, wherein the one or more processors execute instructions to:   receive data;   generate, using the data, a plurality of input data incidents;   store, on the database, the plurality of input data incidents;   generate, for each input data incident of the plurality of input data incidents, one or more potential data outputs;   construct, for each input data incident of the plurality of input data incidents, a data set of output data incidents using the one or more potential data outputs;   store, on the database, the data set of output data incidents for each input data incident, wherein the server computer system maps each input data incident of the plurality of input data incidents with its corresponding data set of output data incidents.   
     
     
         2 . The system of  claim 1 , wherein each of the plurality of input data incidents represents a relationship between at least two features. 
     
     
         3 . The system of  claim 1 , wherein each of the data set of output data incidents represents a relationship between at least two features. 
     
     
         4 . The system of  claim 1 , wherein the one or more processors execute instructions to:
 perform, for at least one of the plurality of input data incidents, a prediction operation based on a corresponding data set of output data incidents.   
     
     
         5 . The system of  claim 4 , wherein the one or more processors execute instructions to:
 display a result of the prediction operation.   
     
     
         6 . The system of  claim 4  wherein the data is received within a query, and wherein the prediction operation is performed in response to receiving the query. 
     
     
         7 . The system of  claim 6 , wherein the at least one of the plurality of input data incidents corresponds to a first time period, and wherein the corresponding data set of corresponds to a second time period. 
     
     
         8 . The system of  claim 7 , wherein the first time period and the second time period occur before the query is received. 
     
     
         9 . The system of  claim 1 , wherein generating the plurality of input data incidents includes:
 identifying features of interest in the data; and   categorizing the data in accordance with the features of interest.   
     
     
         10 . The system of  claim 1 , wherein generating the data set of output data incidents includes:
 identifying at least a subset of the data that corresponds to at least one of the one or more potential data outputs.   
     
     
         11 . A method comprising:
 receiving data;   generating, using the data, a plurality of input data incidents;   storing, on a database, the plurality of input data incidents;   generating, for each input data incident of the plurality of input data incidents, one or more potential data outputs;   constructing, for each input data incident of the plurality of input data incidents, a data set of output data incidents using the one or more potential data outputs;   storing, on the database, the data set of output data incidents for each input data incident by mapping each input data incident of the plurality of input data incidents with its corresponding data set of output data incidents.   
     
     
         12 . The method of  claim 11 , wherein each of the plurality of input data incidents represents a relationship between at least two features. 
     
     
         13 . The method of  claim 11 , wherein each of the data set of output data incidents represents a relationship between at least two features. 
     
     
         14 . The method of  claim 11 , further comprising performing, for at least one of the plurality of input data incidents, a prediction operation based on a corresponding data set of output data incidents. 
     
     
         15 . The method of  claim 14 , further comprising displaying a result of the prediction operation. 
     
     
         16 . The method of  claim 14 , wherein the data is received within a query, and wherein the prediction operation is performed in response to receiving the query. 
     
     
         17 . The method of  claim 16 , wherein the at least one of the plurality of input data incidents corresponds to a first time period, and wherein the corresponding data set of corresponds to a second time period. 
     
     
         18 . The method of  claim 17 , wherein the first time period and the second time period occur before the query is received. 
     
     
         19 . The method of  claim 11 , wherein generating the plurality of input data incidents includes:
 identifying features of interest in the data; and   categorizing the received data in accordance with the features of interest.   
     
     
         20 . The method of  claim 11 , wherein generating the data set of output data incidents includes:
 identifying at least a subset of the data that corresponds to at least one of the one or more potential data outputs.