Event Sequence Indexing With Bit Vectors for Real-Time Analytics
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Solution Overview
Problem
Existing contact center systems face high computational complexity and scalability issues in querying and filtering large numbers of event sequences, leading to inefficient user-friendly visualizations and analytics.
Innovation Solution
The implementation of optimized event sequence indices, including inverted and forward search indices, which utilize bit vectors to encode event patterns, allowing for efficient filtering and querying of event sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional query methods are used to search and filter event sequences, then the system can handle basic analytics requirements, but the computational complexity increases significantly and scalability deteriorates when dealing with large numbers of event sequences
Solution Approach 1:
The system pre-computes and stores event sequence data in optimized index structures (inverted indexes, forward indexes, and bit vector encodings) before queries are executed. This preliminary organization of data allows rapid retrieval and filtering operations without performing complex computations during actual query execution, thereby improving query efficiency while managing computational complexity.
Solution Approach 2:
The patent creates multiple indexed copies of event sequence data in different formats (inverted indexes for reverse lookup, forward indexes for sequential access, and bit vector representations for compact storage). These copied and reorganized versions enable efficient querying without processing the original large-scale event data, thus enhancing productivity without proportionally increasing computational complexity.
2Productivity
If traditional event sequence storage and retrieval methods are used, then the system can maintain data integrity, but scalability deteriorates when handling large volumes of event data for real-time analytics
Solution Approach 1:
The event sequence data is segmented and organized into multiple independent index structures including inverted indexes (mapping events to sequences), forward indexes (mapping sequences to events), and bit vector encodings. This segmentation allows the system to scale by processing only relevant portions of data during queries rather than scanning entire datasets, thereby improving scalability while maintaining fast query response times.
Solution Approach 2:
The patent transforms event sequence data into different parameter representations through indexing and encoding. By converting raw event data into structured index formats with optimized access patterns, the system enables scalable handling of large volumes of event data while reducing query time through efficient parameter-based retrieval operations.
3Measurement precision
If comprehensive event sequence data is retained for detailed analytics, then measurement precision is improved, but the system complexity and resource requirements increase
Solution Approach 1:
The system creates multiple specialized copies of event sequence data in different index formats (inverted indexes for event-to-sequence mapping, forward indexes for sequence-to-event mapping, and bit vector encodings for compact representation). Each copy is optimized for specific analytics operations, enabling precise measurements and detailed analysis without requiring the system to maintain and process all raw data simultaneously, thus managing system complexity while preserving analytics precision.
Data Source
AI summary
A method for generating an inverted search index for event sequence visualization may include determining, from an event sequence dataset containing event sequences and events, event pair combinations based on identified unique singleton events. The method may further include establishing a positional ordering for each singleton event and each event pair combination and generating a respective event sequence set for each event sequence. The method may also include determining whether each unique singleton event and each event pair combination exists or does not exist within each event sequence, and populating, for each respective event sequence set and according to the positional ordering, data indicative of whether each unique singleton event and each event pair combination exists or does not exist within the event sequence for the respective event sequence set. The method may also include generating the inverted search index including each respective event sequence set for each event sequence.