Clickstream Visual Analytics Using Maximal Sequential Patterns
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Solution Overview
Problem
Traditional clickstream analytics applications are inadequate for summarizing large volumes of complex data, failing to provide concise summaries of user interactions with modern websites and software applications.
Innovation Solution
The system analyzes clickstream data to identify navigational patterns and presents them in a visual, easily navigable interface, allowing analysts to pinpoint path segments of interest for further analysis by using a maximal sequential pattern algorithm and interactive navigational frameworks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional clickstream analytics applications are used to summarize clickstreams, then the analysis process is simple, but the summarization becomes insufficient when dealing with voluminous amounts of data
Solution Approach 1:
The patent segments the clickstream data into distinct navigational patterns by identifying sequential relationships between resources. Instead of treating the entire clickstream as a single complex data structure, the system divides it into recognizable patterns (e.g., sequential access sequences, navigational paths) that can be individually analyzed and summarized, thereby maintaining information integrity while simplifying the analysis process.
Solution Approach 2:
The patent extracts navigational patterns from the voluminous clickstream data by identifying and isolating sequential relationships between resources. This extraction process pulls out meaningful navigational information (such as common user paths, resource access sequences) from the raw data, creating condensed representations that preserve essential information while reducing data volume for analysis.
2Ease of operation
If traditional simple flow diagrams are used for summarization, then the visual interface is easy to understand, but the diagrams cannot concisely summarize voluminous clickstream data
Solution Approach 1:
The patent transitions from traditional two-dimensional flow diagrams to a multi-dimensional visual representation system that incorporates hierarchical levels, temporal dimensions, and navigational pattern classifications. This dimensional expansion allows the visual interface to encode and display voluminous clickstream data in a structured manner that maintains ease of understanding while significantly increasing data summarization capacity through layered and organized visual presentations.
3Measurement precision
If clickstream data is analyzed in detail to identify navigational patterns, then the analysis depth increases, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing clickstream data to identify and index navigational patterns before detailed analysis is required. The system pre-segments data into navigational patterns, pre-ranks them by frequency or importance, and pre-organizes them for efficient retrieval, thereby reducing processing time during subsequent detailed analysis while maintaining high measurement precision for pattern identification.
Data Source
AI summary
Systems and methods are disclosed for analyzing a plurality of clickstreams associated with a resource to identify popular navigational patterns traversed by users of the resource. The analysis provides a navigational framework for performing continued analysis on segmented portions of the identified navigational patterns. To facilitate the analysis, clickstreams associated with the resource are analyzed to identify sets of clickstreams that have a common group of assets with which users of the resource interacted. Navigational patterns, which include commonly traversed series of assets interacted with by the users, are determined for the identified sets. The navigational pattern is then provided to identify popular navigational patterns traversed by users of the resource.