Object Model Preloading for Faster Document Viewing
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Solution Overview
Problem
Conventional document viewing systems are inefficient in handling large document corpora, requiring serial review of individual documents, leading to significant delays in loading and processing times, which wastes user time and increases impatience.
Innovation Solution
A method involving the generation of object models with metadata, predictive processing to create cached document models, and rendering these models via a viewport to improve document preloading and display efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional serial document review is used, then each document can be reviewed individually, but the loading and processing delays accumulate significantly when reviewing large document corpora
Solution Approach 1:
The system performs preliminary processing of document models by generating object models with metadata and pre-processing them into cached document models before they are actually needed for review. This advance preparation eliminates loading delays during the review process, as documents are ready for immediate display when requested.
Solution Approach 2:
The document processing is divided into distinct segments: object model generation, metadata extraction, predictive processing, and cached model creation. This segmentation allows different stages of document preparation to occur independently and in parallel, reducing overall processing time when reviewing multiple documents.
2Productivity
If multiple documents are pre-loaded concurrently, then document review speed improves, but system resource requirements and processing complexity increase
Solution Approach 1:
Documents are pre-processed into cached models in advance, storing essential information in an optimized format. This preliminary action simplifies the actual review process, as the system only needs to retrieve and display pre-processed models rather than processing full documents in real-time.
Solution Approach 2:
The system creates cached copies of document models that contain pre-extracted metadata and processed information. These copies are stored in an optimized format that is easier and faster to retrieve and display than the original documents, reducing the computational complexity during review.
3Loss of time
If object models with metadata are generated and predictively processed, then document display latency is reduced, but initial processing time and computational resources increase
Solution Approach 1:
The system performs computationally intensive object model generation and metadata extraction in advance, when the system is idle or during off-peak periods. This shifts the energy consumption to a different time, reducing the perceived latency during actual document review operations.
Solution Approach 2:
The system automatically manages the pre-processing of document models without requiring manual intervention. It intelligently determines which documents to pre-process based on access patterns and system resources, optimizing the balance between processing effort and performance benefit.
Data Source
AI summary
A computer-implemented method includes generating a user interface; receiving a set of object models; processing the received object models; and rendering the document model via a viewport. A non-transitory computer readable medium contains program instructions that when executed, cause a computer to generate a user interface; receive a set of object models; process the received object models; and render the document model via a viewport. A computing system includes a processor and a memory having stored thereon instructions that when executed by the process, cause the computing system to generate a user interface; receive a set of object models; process the received object models; and render the document model via a viewport.