Time Gram Encoding System for Event Time Series Analysis
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Solution Overview
Problem
Conventional methods for encoding event time series fail to consider inter-arrival times between events, resulting in incomplete pattern recognition and failure to capture temporal dimensions in data analysis.
Innovation Solution
A system that computes inter-arrival times, transforms them into discrete symbols, and maps these symbols using a dictionary to generate 'time grams,' which encode both event sequences and time gaps, enabling more comprehensive pattern recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional methods are used to encode event time series, then the encoding process is simple and fast, but the temporal dimension and inter-arrival times between events are not captured
Solution Approach 1:
The encoding system segments the continuous inter-arrival time into discrete time symbols by dividing the time range into multiple bins. Each bin represents a discrete time symbol, transforming continuous temporal information into discrete categories that can be processed while preserving the temporal dimension of event sequences
Solution Approach 2:
The patent introduces an intermediary transformation process that converts continuous inter-arrival times into discrete time symbols through a dictionary mapping. This intermediary step bridges the gap between continuous temporal data and discrete event sequences, enabling temporal information to be preserved in the encoded representation
2Measurement precision
If inter-arrival times are transformed into discrete symbols, then pattern recognition accuracy is improved, but the processing complexity increases
Solution Approach 1:
The system changes the parameter representation of inter-arrival times from continuous values to discrete symbols by applying a binning transformation. This parameter change enables more precise pattern recognition by preserving temporal distinctions while making the data suitable for discrete sequence processing algorithms
3Loss of information
If a dictionary mapping is used to encode events and time symbols, then the temporal patterns are preserved, but the encoding complexity increases
Solution Approach 1:
The system performs preliminary action by pre-defining a dictionary that maps event types and time symbols to discrete representations before the actual encoding process. This pre-prepared mapping structure enables efficient encoding while preserving temporal patterns, as the transformation rules are established in advance rather than computed in real-time
Data Source
AI summary
An encoding system for encoding an event time series, the system including an inter-arrival time computing device configured to compute an inter-arrival time between a plurality of input events and computes a sequence of events, a transformation device configured to transform the inter-arrival time between the plurality of input events into discrete time symbols, and a mapping device configured to map the input events and the discrete time symbols using a dictionary to output a time gram.