Markup Analysis for Page-Based Document Search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Page-based markup documents require loading and rendering all pages for search operations, leading to excessive memory consumption and lengthy search times, especially when only a subset of pages contains the search string.
Innovation Solution
The system employs an optimized search module that analyzes markup elements to identify candidate pages containing the search string, rendering only these pages and searching within them, thereby reducing memory usage and search time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all pages are loaded and rendered before search, then comprehensive search coverage is achieved, but search time becomes excessively long
Solution Approach 1:
The patent segments the search process into two distinct phases: (1) a markup analysis phase that quickly identifies candidate pages containing the search string by analyzing only the markup structure, and (2) a rendering phase that processes only those identified candidate pages. This segmentation allows the system to achieve comprehensive search coverage while dramatically reducing overall search time by avoiding rendering of pages that do not contain the search term.
Solution Approach 2:
The patent performs preliminary markup analysis on all pages before rendering any pages for full search. This preliminary action identifies which pages contain the search string by analyzing markup elements such as text content, headings, and metadata. By performing this filtering action beforehand, the system prepares a reduced set of candidate pages that need to be fully rendered, thus reducing total search time while maintaining comprehensive coverage.
2Measurement precision
If all pages are loaded into memory, then complete document search is enabled, but memory consumption becomes excessive
Solution Approach 1:
The patent segments memory usage into two distinct pools: (1) a small amount of memory required to store the markup structure and search index for rapid candidate identification, and (2) memory for rendering only the candidate pages that contain the search string. This segmentation enables complete document search coverage while dramatically reducing peak memory consumption by avoiding loading of pages that do not contain the search term.
Solution Approach 2:
The patent extracts and processes only the essential markup elements (such as text content, headings, and metadata) that are necessary for identifying candidate pages containing the search string. By extracting only these critical elements for the search phase and separating them from the full page rendering process, the system enables comprehensive search while minimizing memory consumption during the search operation.
3Ease of operation
If pages are rendered for display before search, then visual formatting is preserved, but search performance deteriorates
Solution Approach 1:
The patent segments the processing pipeline into distinct markup analysis and rendering phases. During the markup analysis phase, only the structural markup elements are processed to identify candidate pages, preserving visual formatting information without actually rendering the pages. During the subsequent rendering phase, only the identified candidate pages are rendered with full visual formatting. This segmentation maintains ease of operation by preserving visual presentation while dramatically improving search speed by avoiding premature rendering of all pages.
Data Source
AI summary
Systems, methods, and/or techniques (“tools”) for improved search techniques for page-based document layouts are described herein. The tools may analyze markup elements defined for pages within source documents, and may determine whether the markup elements for the page may include at least part of a search string.