Document Snippet Navigation Using Robust Fragment Identifiers
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Solution Overview
Problem
Current methods for identifying specific content within documents using fragment identifiers are inefficient and prone to errors, particularly due to dynamic changes in document content and the reliance on position-based schemes that are susceptible to link rot and require lengthy URIs, which can lead to inaccurate or broken links.
Innovation Solution
The use of rolling n-gram hashes and canonical forms to create robust and concise fragment identifiers that remain effective even with dynamic document changes, allowing for efficient and reliable identification of content without growing in length with the identified content, and enabling precise navigation to specific snippets within documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If position-based fragment identifiers are used to identify content in documents, then the identification method is simple to implement, but the identifiers become lengthy and susceptible to link rot when document content changes dynamically
Solution Approach 1:
The patent changes the fundamental parameter used for fragment identification from position-based indexing to content-based hashing. Instead of using numerical positions that change with document modifications, the system computes hash values from the actual content text, creating stable identifiers that remain valid even when document structure changes. This transforms the identification mechanism from fragile position-dependent to robust content-dependent.
Solution Approach 2:
The patent creates a hash copy of the content rather than directly using the content itself as the identifier. This hash copy serves as a compact, stable representation that can be used for identification without exposing the full content. The hash function creates a condensed version that maintains the uniqueness and reliability properties needed for accurate content identification.
2Reliability
If content-based fragment identifiers are used to remain robust against document changes, then link reliability improves, but the computation and storage requirements increase
Solution Approach 1:
The patent replaces complex content comparison operations with simple hash value comparisons. Instead of comparing entire content strings or performing sophisticated matching algorithms, the system computes hash values and compares these condensed representations. This substitution dramatically reduces computational complexity while maintaining the reliability of content-based identification.
Solution Approach 2:
The patent transforms the content identification problem by changing from direct content manipulation to hash-based representation. This parameter change converts high-complexity string operations into low-complexity numerical comparisons, making the system scalable and efficient while preserving the robustness of content-based identification.
3Ease of operation
If traditional find functionality is used to locate content in documents, then users can search for text strings, but the process is manual and time-consuming
Solution Approach 1:
The patent performs preliminary computation of hash values for all content segments during document processing or indexing. This advance preparation creates a ready-to-use mapping between hash values and content locations, eliminating the need for manual searching. When users need to locate content, they simply compute or provide the hash value, and the system instantly retrieves the pre-computed location information.
Solution Approach 2:
The patent introduces hash values as an intermediary between user queries and content locations. Instead of directly searching through document text, users interact with hash-based identifiers that serve as efficient mediators. This intermediary layer enables rapid content retrieval by translating user intent into precise location information through hash comparison, dramatically reducing search time.
Data Source
AI summary
A computer-implemented system and method for search and navigation on a network to find and display specific search identified information in documents. Queries are sent to search engine services and responses comprising snippets are returned. Then, in response to only one or a few user inputs, documents are opened and locations of content matching or best matching the snippets are found reliably and distinguished in a display.