Universal Data Log Analyzer for Web Page Journey Mapping
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Solution Overview
Problem
Existing data log analysis systems struggle to provide universal organization and analysis of user interaction data across different websites due to variations in programming languages, style sheets, and attribute definitions, leading to inconsistencies in data log formats and lack of identification of page flows or state transitions.
Innovation Solution
A data log analyzer processes data logs with unknown formats to generate page journey information, including descriptions of attributes, sequences of web resources, and semantic labels, by identifying frequent attribute-value pairs and grouping them into page states and user sessions, and aggregating page paths to provide insights into user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data logs from different websites are analyzed using traditional methods, then analysis can be performed on individual websites, but universal organization and analysis across multiple websites cannot be achieved due to format variations
Solution Approach 1:
The patent creates a universal data log organization system that can handle multiple website data formats through a common schema. The system defines standardized attribute categories (page state attributes, user session attributes, web resource attributes) that can organize data from any website regardless of its original format, making the analysis system universally applicable across different websites and programming languages
Solution Approach 2:
The system transforms heterogeneous data log formats into a standardized parameter structure by mapping various website-specific attributes to universal attribute categories. This parameter transformation allows the system to accommodate different data formats while maintaining consistent analysis capabilities across all inputs
2Loss of information
If detailed analysis of all data log attributes is performed, then comprehensive user interaction information can be obtained, but identification of page flows and state transitions becomes difficult
Solution Approach 1:
The patent segments the complex data log attributes into distinct functional categories: page state attributes (identifying page states and transitions), user session attributes (tracking user interactions), and web resource attributes (describing accessed resources). This segmentation allows the system to maintain complete attribute information while making page flows and state transitions easily identifiable through the structured organization
Solution Approach 2:
The patent introduces an intermediary organizational layer (the standardized attribute schema) between the raw data logs and the analysis process. This intermediary structure acts as a mediator that preserves all original attribute information while organizing it in a way that makes page flows and state transitions detectable through the relationships defined in the schema
3Loss of information
If page journey information is generated for all users, then comprehensive user experience insights can be obtained, but processing time and computational resources increase
Solution Approach 1:
The patent implements a two-level analysis approach where page states and sessions are identified for all users (complete action), but page journey aggregation and analysis can be applied selectively to specific user groups, time periods, or traffic patterns (partial action). This allows the system to maintain complete data collection capabilities while enabling flexible, resource-efficient analysis based on specific analytical needs
Data Source
AI summary
Large amounts of data from user interactions with web resources is available as data logs. Analysis may be performed to process the data log in order to determine the characteristics of the user interactions. Data log analysis may include identifying page states, which may be sets of frequent attributes and values that occur together in a session. The data log analysis may also include generating semantic labels of page states, which may describe the function of pages corresponding to different page states. Text mining models may be used to determine the semantic labels. Analysis may also include aggregating sets of page paths to create page journeys. These page journeys may be aggregated over all users, all user sessions, or other subsets of the clickstream. In some embodiments, comparing page journeys may provide recommendations for potential methods to improve the site and enhance user experiences.