Document Search Indexing via Event Context Segmentation
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Solution Overview
Problem
Existing document search systems require accurate memory of document content and are burdened by large search results, especially when searching for documents used in specific contexts like conferences, where detailed context information increases search time and complexity.
Innovation Solution
An information processing system that includes a recognition portion for documents, a detection portion for events in a given space, and an index-giving portion that associates event information with documents for efficient searching, allowing users to reconstruct the situation of document usage even if they cannot remember the content accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If character strings in documents are indexed for fast access, then search speed is improved, but the user must remember the exact character string content and receives a large amount of search results that are burdensome
Solution Approach 1:
The patent segments the search index into two distinct components: traditional character string indexes for fast text matching, and event context indexes that capture situational information (participants, locations, time, activities). This segmentation allows users to search using either exact text or contextual cues, resolving the contradiction between search speed and content recall accuracy.
Solution Approach 2:
The patent introduces event context information as an intermediary between the user's imperfect memory and the document database. Instead of requiring direct matching between user query and document content, the event context acts as a mediator that bridges the gap, enabling users to retrieve documents through situational descriptions even when they cannot recall exact text.
2Measurement precision
If detailed context information about document usage is stored, then search accuracy is improved, but it takes more time for the user to find needed information among increased context data
Solution Approach 1:
The patent segments event context information into structured, discrete elements (participants, locations, time, activities, relationships) that can be independently indexed and queried. This segmentation allows the system to process and search context data efficiently, preventing the retrieval time from increasing proportionally with the amount of detailed context stored.
Solution Approach 2:
The patent transforms unstructured context information into structured parameters with defined attributes and relationships. By changing the parameter structure of context data (from free-text descriptions to standardized fields with hierarchical relationships), the system enables faster comparison and matching operations, reducing retrieval time despite increased detail.
3Ease of operation
If event information is associated with documents as search indexes, then documents can be searched without precise content recall, but the device complexity increases
Solution Approach 1:
The patent implements a universal indexing framework that handles both traditional character string searches and event context searches through a unified structure. The event context index uses the same fundamental data structures and search algorithms as traditional indexes, but extends them to accommodate contextual information. This multi-functionality reduces the apparent complexity by reusing existing components rather than creating separate systems.
Solution Approach 2:
The patent performs preliminary action by automatically extracting and structuring event context information during document ingestion, before the search operation occurs. Contextual elements such as participants, locations, and activities are identified and organized in advance, so that during search operations, the system only needs to perform matching rather than complex analysis, thereby reducing operational complexity.
Data Source
AI summary
An information processing system includes a recognition portion that recognizes a document shown in a given space, a detection portion that detects an event occurring in the given space, and an index-giving portion that gives information on the event detected by the detection portion to the information on the document recognized by the recognition portion, as an index for search.