Document Request Overlap Detection and Consolidation
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Solution Overview
Problem
Existing systems face inefficiencies in identifying and managing overlapping document requests across multiple requests, leading to significant storage and maintenance costs due to duplicate document storage and indexing, particularly in large corporations dealing with multiple litigations and document production requirements.
Innovation Solution
A computer-implemented method that generates and compares data object instances to identify overlapping portions, modifies requests to exclude these overlaps, and updates instances with previously identified document locations and content, allowing for centralized management of document access and litigation holds, thereby reducing duplication and burden on individual users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple separate requests for documents are processed independently, then each request can be fulfilled completely, but significant storage and maintenance costs are incurred due to duplicate document storage and indexing
Solution Approach 1:
The system merges overlapping document requests by identifying common time spans, custodians, and document types across multiple requests. When overlap is detected, the system consolidates the requests into a single unified request, retrieving documents once and making them available to all requesting parties. This eliminates duplicate storage and indexing operations while ensuring all requests are fulfilled completely.
Solution Approach 2:
The system performs preliminary analysis of incoming document requests to identify potential overlaps before actual document retrieval occurs. By comparing request parameters (time spans, custodians, document types) in advance, the system can pre-determine which requests can be merged, avoiding unnecessary duplicate retrieval and storage operations.
2Loss of information
If duplicate document requests are fulfilled separately, then each request receives complete documentation, but substantial expenditures are incurred to maintain duplicate images and indexes
Solution Approach 1:
Instead of storing multiple physical copies of duplicate documents, the system creates virtual copies through references or pointers to the single stored instance. When a document is retrieved once to satisfy an overlapping request, subsequent requests receive copies of the retrieval result rather than triggering additional storage operations. This maintains complete document delivery while minimizing actual storage resource consumption.
3Ease of operation
If individual users manage their own document production, then each user maintains control over their documents, but administrative burdens increase significantly for large corporations
Solution Approach 1:
The system introduces a centralized intermediary service that manages document request coordination between multiple users and the document storage system. This intermediary automatically detects overlapping requests, merges them when appropriate, and coordinates fulfillment. Individual users retain control over their documents through authorized access, while the intermediary handles the complex administrative tasks of request management and overlap detection, reducing the burden on both users and system administrators.
4Productivity
If all document requests are processed without overlap detection, then processing is simple and fast, but significant resources are wasted on redundant document production
Solution Approach 1:
The system applies partial overlap detection only to the extent necessary to identify and merge significant duplications. Rather than performing exhaustive analysis of every possible overlap scenario, the system focuses on detecting and resolving the most common and resource-intensive types of overlaps (same custodian, overlapping time spans, identical document types). This selective approach maintains high processing speed while eliminating the most wasteful redundant operations.
Data Source
AI summary
A method, apparatus, and computer-readable medium are described that reduce overlapping portions of data object instances. The data object instances may include requests for identifying locations of stored documents. By comparing a second data object instance to one or more first data object instances, one or more overlapping portions may be removed from the second data object instance. Once the second data object instance is returned with locations of newly identified locations of documents, the removed portions of the second data object instance may be added back with previously identified locations of the documents.