Selective Event Indexing for Real-Time Search Performance
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Solution Overview
Problem
Conventional client-device search applications experience performance degradation due to batch processing, result in outdated indexes, and inefficient searches, as they typically index all articles separately, require explicit queries, and lack real-time distinction between user interactions.
Innovation Solution
The system selectively indexes event data by capturing events associated with articles, evaluating them against criteria to determine indexability, and storing only indexable events, allowing for real-time and historical event management with implicit and explicit query generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If batch processing is used to index all articles, then the index can be maintained, but client-device performance degrades and recent articles may not be included in search results
Solution Approach 1:
The patent segments the indexing process by creating separate indexes for different article types (e.g., emails, web pages, documents) and implementing real-time indexing for specific article types while maintaining batch processing for others. This allows the system to maintain index reliability while improving client-device performance through selective real-time processing.
Solution Approach 2:
The system dynamically adjusts indexing behavior based on article type and user needs. Real-time indexing is applied dynamically to articles that require immediate availability, while batch processing continues for other article types. This dynamic approach resolves the contradiction by adapting the indexing strategy to current system state and requirements.
2Loss of information
If all articles are indexed separately as separate entities, then complete article information is stored, but search becomes time-consuming and inefficient
Solution Approach 1:
The patent merges related articles into unified search results by creating a comprehensive index structure that groups articles by type and content. Instead of processing each article as a completely separate entity, the system combines articles of the same type and creates integrated search results, reducing search time while maintaining information completeness.
Solution Approach 2:
The system changes the indexing parameters by creating different index structures for different article types and using weighted scoring mechanisms. Articles are indexed with different levels of detail based on their type and importance, allowing efficient search while preserving necessary information. This parameter optimization reduces search time without losing critical article information.
3Ease of operation
If conventional search applications require explicit search queries, then search results can be generated, but the system cannot distinguish between real-time and historical user interactions
Solution Approach 1:
The system performs self-service by automatically generating implicit search queries based on user interactions. Instead of requiring explicit queries, the system monitors user behavior (opening, reading, modifying articles) and automatically creates search results, preserving interaction timing information. This eliminates the need for explicit queries while maintaining the ability to distinguish between real-time and historical interactions.
Data Source
AI summary
Methods and systems are provided for selectively storing event data. In one described method, an event associated with an article is captured. The captured event can comprise event data. The method further comprises evaluating the event for satisfaction of a criterion. If the event satisfies the criterion, it is indexed.