Data Log Analyzer for Universal Page Journey Determination
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current 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 from various formats to generate page journey information, including page states and semantic labels, by identifying frequent attribute-value pairs, grouping them into page states, and aggregating page paths to provide insights into user interactions, enabling improvements in user experience and website optimization.
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 different 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 data structures (e.g., visit records, page state records with standardized fields like url, title, timestamp) that can represent data from different websites regardless of their original format variations, enabling one system to serve multiple websites universally
Solution Approach 2:
The system transforms diverse data log formats by mapping various website-specific attributes to standardized parameters. By changing the representation parameters to a universal schema (e.g., mapping different URL formats to a common url field, different timestamp formats to standardized time stamps), the system achieves format adaptability without requiring complex format-specific processing logic
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 without standardized organization
Solution Approach 1:
The patent segments user interaction data into distinct record types with specific purposes: visit records for page access events, page state records for state transitions, and structured fields for specific attributes. This segmentation organizes the detailed attribute data into manageable units, making it easier to detect and measure page flows by tracking sequences of these segmented records
Solution Approach 2:
The standardized data structure acts as an intermediary layer between the raw diverse data logs and the analysis processes. By introducing this intermediate standardized format with explicit fields for URL, title, timestamp, and state information, the system mediates the transformation from unorganized detailed attributes to structured data that reveals page flows and state transitions
3Measurement precision
If custom analysis methods are developed for each website's specific format, then accurate analysis for that website can be achieved, but the analysis process becomes time-consuming and cannot be applied universally
Solution Approach 1:
The patent develops a universal analysis system that maintains measurement precision by using standardized data structures that capture essential user interaction information. The same analysis code can process data from any website that conforms to the standardized format, achieving both precision (through comprehensive standardized fields) and productivity (through format-agnostic processing)
Solution Approach 2:
The system performs preliminary organization of data into standardized formats before analysis. By pre-structuring the data with standardized fields (url, title, timestamp, state) during data collection or initial processing, the subsequent analysis operations can proceed efficiently without needing to parse or interpret various custom formats, thus improving productivity while maintaining precision
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.