A spatial and temporal memory system (STMS) processes input data to detect whether spatial patterns and/or temporal sequences of spatial patterns exist within the data, and to make predictions about future data. The data processed by the STMS may be retrieved from, for example, one or more database fields and is encoded into a distributed representation format using a coding scheme. The performance of the STMS in predicting future data is evaluated for the coding scheme used to process the data as performance data. The selection and prioritization of STMS experiments to perform may be based on the performance data for an experiment. The best fields, encodings, and time aggregations for generating predictions can be determined by an automated search and evaluation of multiple STMS systems.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of processing data, comprising accessing at least one field of data from one or more data sources including a plurality of records of data; encoding, by an encoder, the at least one field of data into encoded input data; generating one or more sparse vectors in a sparse distributed representation format corresponding to the encoded input data, wherein each sparse vector comprises a greater number of inactive elements than active elements; and detecting spatial patterns or temporal sequences of spatial patterns in the one or more sparse vectors at a processing node. 2. The method of claim 1, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on an inhibition range associated with the encoder, the inhibition range defining a number of sparse vector elements adjacent to an active element inhibited from being active. 3. The method of claim 1, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on a pre-defined permissible sparsity threshold. 4. The method of claim 1, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on match scores comprising a degree of detected similarity between spatial patterns within the encoded input data and stored spatial patterns. 5. The method of claim 1, wherein the at least one field of data includes an entry represented by a scalar value, and wherein the encoding comprises determining whether the scalar value is within one or more buckets, wherein each bucket defines a numerical range. 6. The method of claim 5, wherein at least two buckets have overlapping numerical ranges. 7. The method of claim 1, wherein encoding the at least one field of data comprises preprocessing the at least one field of data to generate preprocessed data, and wherein generating the one or more sparse vectors comprises converting the preprocessed data into a sparse distributed representation format. 8. The method of claim 7, wherein preprocessing the at least one field of data comprises performing time aggregation on at least a subset of the at least one field of data to generate the preprocessed data. 9. A system for processing data, the system comprising a data access module configured to access at least one field of data from one or more data sources including a plurality of records of data; an encoder configured to encode the at least one field of data into encoded input data; a sparsity generator configured to generate one or more sparse vectors in a sparse distributed representation format corresponding to the encoded input data, wherein each sparse vector comprises a greater number of inactive elements than active elements; and a processing node configured to detect spatial patterns or temporal sequences of spatial patterns in the one or more sparse vectors at a processing node. 10. The system of claim 9, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on an inhibition range associated with the encoder, the inhibition range defining a number of sparse vector elements adjacent to an active element inhibited from being active. 11. The method of claim 9, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on a pre-defined permissible sparsity threshold. 12. The method of claim 9, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on match scores comprising a degree of detected similarity between spatial patterns within the encoded input data and stored spatial patterns. 13. A non-transitory computer-readable storage medium storing executable computer program instructions for processing data, the instructions comprising instructions for: accessing at least one field of data from one or more data sources including a plurality of records of data; encoding, by an encoder, the at least one field of data into encoded input data; generating one or more sparse vectors in a sparse distributed representation format corresponding to the encoded input data, wherein each sparse vector comprises a greater number of inactive elements than active elements; and detecting spatial patterns or temporal sequences of spatial patterns in the one or more sparse vectors at a processing node. 14. The non-transitory computer-readable storage medium of claim 13, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on an inhibition range associated with the encoder, the inhibition range defining a number of sparse vector elements adjacent to an active element inhibited from being active. 15. The non-transitory computer-readable storage medium of claim 13, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on a pre-defined permissible sparsity threshold. 16. The non-transitory computer-readable storage medium of claim 13, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on match scores comprising a degree of detected similarity between spatial patterns within the encoded input data and stored spatial patterns. 17. A method of processing data, comprising accessing configuration information identifying: an encoder configuration, a portion of data to be processed, and a time aggregation of data; configuring an encoder based on the identified encoder configuration; accessing one or more fields of data based on the identified portion of data; performing a time aggregation on the accessed fields of data based on the identified time aggregation; and encoding, by the encoder, the time aggregated data into a distributed representation format based on the configuration of the encoder. 18. The method of claim 17, wherein the distributed representation format comprises a sparse distributed representation format. 19. The method of claim 18, wherein the sparse distributed representation format comprises a ratio of active elements to inactive elements selected based on a pre-defined permissible sparsity threshold. 20. The method of claim 17, further comprising: detecting spatial patterns or temporal sequences of spatial patterns within the encoded data at a processing node.